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Gaire TN, Odland C, Zhang B, Slizovskiy I, Jorgenson B, Wehri T, Meneguzzi M, Wass B, Schuld J, Hanson D, Doster E, Singer J, Cannon J, Asmus A, Ray T, Dee S, Nerem J, Davies P, Noyes NR. Slaughtering processes impact microbial communities and antimicrobial resistance genes of pig carcasses. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 946:174394. [PMID: 38955276 DOI: 10.1016/j.scitotenv.2024.174394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 06/27/2024] [Accepted: 06/28/2024] [Indexed: 07/04/2024]
Abstract
Several steps in the abattoir can influence the presence of microbes and associated resistance genes (ARGs) on the animal carcasses used for further meat processing. We investigated how these processes influence the resistome-microbiome of groups of pigs with different on-farm antimicrobial exposure status, from the moment they entered the abattoir until the end of carcass processing. Using a targeted enrichment metagenomic approach, we identified 672 unique ARGs conferring resistance to 43 distinct AMR classes from pooled skin (N = 42) and carcass swabs (N = 63) collected sequentially before, during, and after the slaughter process and food safety interventions. We observed significant variations in the resistome and microbial profiles of pigs before and after slaughter, as well as a significant decline in ARG counts, diversity, and microbial DNA load during slaughter and carcass processing, irrespective of prior antimicrobial treatments on the farm. These results suggest that existing interventions in the abattoir are effective in reducing not only the pathogen load but also the overall bacterial burden, including ARGs on pork carcasses. Concomitant with reductions in microbial and ARG counts, we observed an increase in the relative abundance of non-drug-specific ARGs, such as those conferring resistance to metals and biocides, and in particular mercury. Using a strict colocalization procedure, we found that most mercury ARGs were associated with genomes from the Pseudomonadaceae and Enterobacteriaceae families. Collectively, these findings demonstrate that slaughter and processing practices within the abattoir can shape the microbial and ARG profiles of pork carcasses during the transition from living muscle to meat.
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Affiliation(s)
- Tara N Gaire
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | - Carissa Odland
- Pipestone Veterinary Services, Pipestone, MN, USA; Wholestone Farms, NE, USA
| | - Bingzhou Zhang
- State Key Laboratory of Agricultural Microbiology, College of Animal Sciences and Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, China
| | - Ilya Slizovskiy
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | - Blake Jorgenson
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | - Thomas Wehri
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | - Mariana Meneguzzi
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | - Britta Wass
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | | | - Dan Hanson
- Pipestone Applied Research, Pipestone, MN, USA
| | - Enrique Doster
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | - Jacob Singer
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | | | - Aaron Asmus
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA; Hormel Foods, Austin, MN, USA
| | - Tui Ray
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | - Scott Dee
- Pipestone Applied Research, Pipestone, MN, USA
| | - Joel Nerem
- Pipestone Applied Research, Pipestone, MN, USA
| | - Peter Davies
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | - Noelle R Noyes
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA.
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2
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Andersson D, Kebede FT, Escobar M, Österlund T, Ståhlberg A. Principles of digital sequencing using unique molecular identifiers. Mol Aspects Med 2024; 96:101253. [PMID: 38367531 DOI: 10.1016/j.mam.2024.101253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 01/26/2024] [Accepted: 02/03/2024] [Indexed: 02/19/2024]
Abstract
Massively parallel sequencing technologies have long been used in both basic research and clinical routine. The recent introduction of digital sequencing has made previously challenging applications possible by significantly improving sensitivity and specificity to now allow detection of rare sequence variants, even at single molecule level. Digital sequencing utilizes unique molecular identifiers (UMIs) to minimize sequencing-induced errors and quantification biases. Here, we discuss the principles of UMIs and how they are used in digital sequencing. We outline the properties of different UMI types and the consequences of various UMI approaches in relation to experimental protocols and bioinformatics. Finally, we describe how digital sequencing can be applied in specific research fields, focusing on cancer management where it can be used in screening of asymptomatic individuals, diagnosis, treatment prediction, prognostication, monitoring treatment efficacy and early detection of treatment resistance as well as relapse.
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Affiliation(s)
- Daniel Andersson
- Sahlgrenska Center for Cancer Research, Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, 413 90, Gothenburg, Sweden
| | - Firaol Tamiru Kebede
- Sahlgrenska Center for Cancer Research, Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, 413 90, Gothenburg, Sweden
| | - Mandy Escobar
- Sahlgrenska Center for Cancer Research, Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, 413 90, Gothenburg, Sweden
| | - Tobias Österlund
- Sahlgrenska Center for Cancer Research, Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, 413 90, Gothenburg, Sweden; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, 413 90, Gothenburg, Sweden; Department of Clinical Genetics and Genomics, Sahlgrenska University Hospital, 413 45, Gothenburg, Sweden
| | - Anders Ståhlberg
- Sahlgrenska Center for Cancer Research, Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, 413 90, Gothenburg, Sweden; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, 413 90, Gothenburg, Sweden; Department of Clinical Genetics and Genomics, Sahlgrenska University Hospital, 413 45, Gothenburg, Sweden.
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3
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Quek ZBR, Ng SH. Hybrid-Capture Target Enrichment in Human Pathogens: Identification, Evolution, Biosurveillance, and Genomic Epidemiology. Pathogens 2024; 13:275. [PMID: 38668230 PMCID: PMC11054155 DOI: 10.3390/pathogens13040275] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 03/11/2024] [Accepted: 03/18/2024] [Indexed: 04/29/2024] Open
Abstract
High-throughput sequencing (HTS) has revolutionised the field of pathogen genomics, enabling the direct recovery of pathogen genomes from clinical and environmental samples. However, pathogen nucleic acids are often overwhelmed by those of the host, requiring deep metagenomic sequencing to recover sufficient sequences for downstream analyses (e.g., identification and genome characterisation). To circumvent this, hybrid-capture target enrichment (HC) is able to enrich pathogen nucleic acids across multiple scales of divergences and taxa, depending on the panel used. In this review, we outline the applications of HC in human pathogens-bacteria, fungi, parasites and viruses-including identification, genomic epidemiology, antimicrobial resistance genotyping, and evolution. Importantly, we explored the applicability of HC to clinical metagenomics, which ultimately requires more work before it is a reliable and accurate tool for clinical diagnosis. Relatedly, the utility of HC was exemplified by COVID-19, which was used as a case study to illustrate the maturity of HC for recovering pathogen sequences. As we unravel the origins of COVID-19, zoonoses remain more relevant than ever. Therefore, the role of HC in biosurveillance studies is also highlighted in this review, which is critical in preparing us for the next pandemic. We also found that while HC is a popular tool to study viruses, it remains underutilised in parasites and fungi and, to a lesser extent, bacteria. Finally, weevaluated the future of HC with respect to bait design in the eukaryotic groups and the prospect of combining HC with long-read HTS.
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Affiliation(s)
- Z. B. Randolph Quek
- Defence Medical & Environmental Research Institute, DSO National Laboratories, Singapore 117510, Singapore
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Cooper AL, Low A, Wong A, Tamber S, Blais BW, Carrillo CD. Modeling the limits of detection for antimicrobial resistance genes in agri-food samples: a comparative analysis of bioinformatics tools. BMC Microbiol 2024; 24:31. [PMID: 38245666 PMCID: PMC10799530 DOI: 10.1186/s12866-023-03148-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 12/07/2023] [Indexed: 01/22/2024] Open
Abstract
BACKGROUND Although the spread of antimicrobial resistance (AMR) through food and its production poses a significant concern, there is limited research on the prevalence of AMR bacteria in various agri-food products. Sequencing technologies are increasingly being used to track the spread of AMR genes (ARGs) in bacteria, and metagenomics has the potential to bypass some of the limitations of single isolate characterization by allowing simultaneous analysis of the agri-food product microbiome and associated resistome. However, metagenomics may still be hindered by methodological biases, presence of eukaryotic DNA, and difficulties in detecting low abundance targets within an attainable sequence coverage. The goal of this study was to assess whether limits of detection of ARGs in agri-food metagenomes were influenced by sample type and bioinformatic approaches. RESULTS We simulated metagenomes containing different proportions of AMR pathogens and analysed them for taxonomic composition and ARGs using several common bioinformatic tools. Kraken2/Bracken estimates of species abundance were closest to expected values. However, analysis by both Kraken2/Bracken indicated presence of organisms not included in the synthetic metagenomes. Metaphlan3/Metaphlan4 analysis of community composition was more specific but with lower sensitivity than the Kraken2/Bracken analysis. Accurate detection of ARGs dropped drastically below 5X isolate genome coverage. However, it was sometimes possible to detect ARGs and closely related alleles at lower coverage levels if using a lower ARG-target coverage cutoff (< 80%). While KMA and CARD-RGI only predicted presence of expected ARG-targets or closely related gene-alleles, SRST2 (which allows read to map to multiple targets) falsely reported presence of distantly related ARGs at all isolate genome coverage levels. The presence of background microbiota in metagenomes influenced the accuracy of ARG detection by KMA, resulting in mcr-1 detection at 0.1X isolate coverage in the lettuce but not in the beef metagenome. CONCLUSIONS This study demonstrates accurate detection of ARGs in synthetic metagenomes using various bioinformatic methods, provided that reads from the ARG-encoding organism exceed approximately 5X isolate coverage (i.e. 0.4% of a 40 million read metagenome). While lowering thresholds for target gene detection improved sensitivity, this led to the identification of alternative ARG-alleles, potentially confounding the identification of critical ARGs in the resistome. Further advancements in sequencing technologies providing increased coverage depth or extended read lengths may improve ARG detection in agri-food metagenomic samples, enabling use of this approach for tracking clinically important ARGs in agri-food samples.
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Affiliation(s)
- Ashley L Cooper
- Research and Development, Ottawa Laboratory (Carling), Canadian Food Inspection Agency, Ottawa, ON, Canada
- Department of Biology, Carleton University, Ottawa, ON, Canada
| | - Andrew Low
- Research and Development, Ottawa Laboratory (Carling), Canadian Food Inspection Agency, Ottawa, ON, Canada
| | - Alex Wong
- Department of Biology, Carleton University, Ottawa, ON, Canada
| | - Sandeep Tamber
- Microbiology Research Division, Bureau of Microbial Hazards, Health Canada, Ottawa, ON, Canada
| | - Burton W Blais
- Research and Development, Ottawa Laboratory (Carling), Canadian Food Inspection Agency, Ottawa, ON, Canada
- Department of Biology, Carleton University, Ottawa, ON, Canada
| | - Catherine D Carrillo
- Research and Development, Ottawa Laboratory (Carling), Canadian Food Inspection Agency, Ottawa, ON, Canada.
- Department of Biology, Carleton University, Ottawa, ON, Canada.
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Castañeda-Barba S, Top EM, Stalder T. Plasmids, a molecular cornerstone of antimicrobial resistance in the One Health era. Nat Rev Microbiol 2024; 22:18-32. [PMID: 37430173 DOI: 10.1038/s41579-023-00926-x] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/08/2023] [Indexed: 07/12/2023]
Abstract
Antimicrobial resistance (AMR) poses a substantial threat to human health. The widespread prevalence of AMR is, in part, due to the horizontal transfer of antibiotic resistance genes (ARGs), typically mediated by plasmids. Many of the plasmid-mediated resistance genes in pathogens originate from environmental, animal or human habitats. Despite evidence that plasmids mobilize ARGs between these habitats, we have a limited understanding of the ecological and evolutionary trajectories that facilitate the emergence of multidrug resistance (MDR) plasmids in clinical pathogens. One Health, a holistic framework, enables exploration of these knowledge gaps. In this Review, we provide an overview of how plasmids drive local and global AMR spread and link different habitats. We explore some of the emerging studies integrating an eco-evolutionary perspective, opening up a discussion about the factors that affect the ecology and evolution of plasmids in complex microbial communities. Specifically, we discuss how the emergence and persistence of MDR plasmids can be affected by varying selective conditions, spatial structure, environmental heterogeneity, temporal variation and coexistence with other members of the microbiome. These factors, along with others yet to be investigated, collectively determine the emergence and transfer of plasmid-mediated AMR within and between habitats at the local and global scale.
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Affiliation(s)
- Salvador Castañeda-Barba
- Department of Biological Sciences, University of Idaho, Moscow, ID, USA
- Bioinformatics and Computational Biology Graduate Program, University of Idaho, Moscow, ID, USA
- Institute for Interdisciplinary Data Sciences, University of Idaho, Moscow, ID, USA
| | - Eva M Top
- Department of Biological Sciences, University of Idaho, Moscow, ID, USA
- Bioinformatics and Computational Biology Graduate Program, University of Idaho, Moscow, ID, USA
- Institute for Interdisciplinary Data Sciences, University of Idaho, Moscow, ID, USA
- Institute for Modelling Collaboration and Innovation, University of Idaho, Moscow, ID, USA
| | - Thibault Stalder
- Department of Biological Sciences, University of Idaho, Moscow, ID, USA.
- Institute for Interdisciplinary Data Sciences, University of Idaho, Moscow, ID, USA.
- Institute for Modelling Collaboration and Innovation, University of Idaho, Moscow, ID, USA.
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Brumfield KD, Usmani M, Santiago S, Singh K, Gangwar M, Hasan NA, Netherland M, Deliz K, Angelini C, Beatty NL, Huq A, Jutla AS, Colwell RR. Genomic diversity of Vibrio spp. and metagenomic analysis of pathogens in Florida Gulf coastal waters following Hurricane Ian. mBio 2023; 14:e0147623. [PMID: 37931127 PMCID: PMC10746180 DOI: 10.1128/mbio.01476-23] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 08/30/2023] [Indexed: 11/08/2023] Open
Abstract
IMPORTANCE Evidence suggests warming temperatures are associated with the spread of potentially pathogenic Vibrio spp. and the emergence of human disease globally. Following Hurricane Ian, the State of Florida reported a sharp increase in the number of reported Vibrio spp. infections and deaths. Hence, monitoring of pathogens, including vibrios, and environmental parameters influencing their occurrence is critical to public health. Here, DNA sequencing was used to investigate the genomic diversity of Vibrio parahaemolyticus and Vibrio vulnificus, both potential human pathogens, in Florida coastal waters post Hurricane Ian, in October 2022. Additionally, the microbial community of water samples was profiled to detect the presence of Vibrio spp. and other microorganisms (bacteria, fungi, protists, and viruses) present in the samples. Long-term environmental data analysis showed changes in environmental parameters during and after Ian were optimal for the growth of Vibrio spp. and related pathogens. Collectively, results will be used to develop predictive risk models during climate change.
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Affiliation(s)
- Kyle D. Brumfield
- Maryland Pathogen Research Institute, University of Maryland, College Park, Maryland, USA
- University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland, USA
| | - Moiz Usmani
- Department of Environmental Engineering Sciences, Geohealth and Hydrology Laboratory, University of Florida, Gainesville, Florida, USA
| | - Sanneri Santiago
- Department of Environmental Engineering Sciences, Engineering School of Sustainable Infrastructure and Environment, University of Florida, Gainesville, Florida, USA
| | - Komalpreet Singh
- Department of Environmental Engineering Sciences, Geohealth and Hydrology Laboratory, University of Florida, Gainesville, Florida, USA
| | - Mayank Gangwar
- Department of Environmental Engineering Sciences, Geohealth and Hydrology Laboratory, University of Florida, Gainesville, Florida, USA
| | | | | | - Katherine Deliz
- Department of Environmental Engineering Sciences, Engineering School of Sustainable Infrastructure and Environment, University of Florida, Gainesville, Florida, USA
| | - Christine Angelini
- Department of Environmental Engineering Sciences, Engineering School of Sustainable Infrastructure and Environment, University of Florida, Gainesville, Florida, USA
| | - Norman L. Beatty
- Department of Medicine, Division of Infectious Diseases and Global Medicine, University of Florida, Gainesville, Florida, USA
| | - Anwar Huq
- Maryland Pathogen Research Institute, University of Maryland, College Park, Maryland, USA
| | - Antarpreet S. Jutla
- Department of Environmental Engineering Sciences, Geohealth and Hydrology Laboratory, University of Florida, Gainesville, Florida, USA
| | - Rita R. Colwell
- Maryland Pathogen Research Institute, University of Maryland, College Park, Maryland, USA
- University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland, USA
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7
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Diaz GR, Gaire TN, Ferm P, Case L, Caixeta LS, Goldsmith TJ, Armstrong J, Noyes NR. Effect of castration timing and weaning strategy on the taxonomic and functional profile of ruminal bacteria and archaea of beef calves. Anim Microbiome 2023; 5:61. [PMID: 38041127 PMCID: PMC10691087 DOI: 10.1186/s42523-023-00284-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 11/28/2023] [Indexed: 12/03/2023] Open
Abstract
BACKGROUND Beef cattle experience several management challenges across their lifecycle. Castration and weaning, two major interventions in the early life of beef cattle, can have a substantial impact on animal performance. Despite the key role of the rumen microbiome on productive traits of beef cattle, the effect of castration timing and weaning strategy on this microbial community has not been formally described. We assessed the effect of four castration time windows (at birth, turnout, pre-weaning and weaning) and two weaning strategies (fence-line and truck transportation) on the rumen microbiome in a randomized controlled study with 32 male calves across 3 collection days (i.e., time points). Ruminal fluid samples were submitted to shotgun metagenomic sequencing and changes in the taxonomic (microbiota) and functional profile (metagenome) of the rumen microbiome were described. RESULTS Using a comprehensive yet stringent taxonomic classification approach, we identified 10,238 unique taxa classified under 40 bacterial and 7 archaeal phyla across all samples. Castration timing had a limited long-term impact on the rumen microbiota and was not associated with changes in alpha and beta diversity. The interaction of collection day and weaning strategy was associated with changes in the rumen microbiota, which experienced a significant decrease in alpha diversity and shifts in beta diversity within 48 h post-weaning, especially in calves abruptly weaned by truck transportation. Calves weaned using a fence-line weaning strategy had lower relative abundance of Bacteroides, Lachnospira, Fibrobacter and Ruminococcus genera compared to calves weaned by truck transportation. Some genes involved in the hydrogenotrophic methanogenesis pathway (fwdB and fwdF) had higher relative abundance in fence-line-weaned calves post-weaning. The antimicrobial resistance gene tetW consistently represented more than 50% of the resistome across time, weaning and castration groups, without significant changes in relative abundance. CONCLUSIONS Within the context of this study, castration timing had limited long-term effects on the rumen microbiota, while weaning strategy had short-term effects on the rumen microbiota and methane-associated metagenome, but not on the rumen resistome.
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Affiliation(s)
- Gerardo R Diaz
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, 55108, USA
| | - Tara N Gaire
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, 55108, USA
| | - Peter Ferm
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, 55108, USA
| | - Lacey Case
- North Central Research and Outreach Center, Department of Animal Science, University of Minnesota, St. Paul, MN, 55108, USA
| | - Luciano S Caixeta
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, 55108, USA
| | - Timothy J Goldsmith
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, 55108, USA
| | - Joe Armstrong
- Agricultural and Natural Resource Systems, University of Minnesota Extension, University of Minnesota, St. Paul, MN, 55108, USA
| | - Noelle R Noyes
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, 55108, USA.
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8
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Šakarnytė L, Šiugždinienė R, Žymantienė J, Ruzauskas M. Comparison of Oral Microbial Composition and Determinants Encoding Antimicrobial Resistance in Dogs and Their Owners. Antibiotics (Basel) 2023; 12:1554. [PMID: 37887255 PMCID: PMC10604839 DOI: 10.3390/antibiotics12101554] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 09/14/2023] [Accepted: 10/19/2023] [Indexed: 10/28/2023] Open
Abstract
Consolidated studies on animal, human, and environmental health have become very important for understanding emerging zoonotic diseases and the spread of antimicrobial resistance (AMR). The aim of this study was to analyse the oral microbiomes of healthy dogs and their owners, including determinants of AMR. Shotgun metagenomic sequencing detected 299 bacterial species in pets and their owners, from which 70 species were carried by dogs and 229 species by humans. Results demonstrated a unique microbial composition of dogs and their owners. At an order level, Bacteroidales were the most prevalent oral microbiota of dogs with significantly lower prevalence in their owners where Actinomycetales and Lactobacillales predominated. Porphyromonas and Corynebacterium were the most prevalent genera in dogs, whereas Streptococcus and Actinomyces were in animal owners. The resistances to macrolides, tetracyclines, lincosamides and Cfx family A class broad-spectrum β-lactamase were detected in both animal and human microbiomes. Resistance determinants to amphenicols, aminoglycosides, sulphonamides, and quaternary ammonium compounds were detected exceptionally in dogs. In conclusion, the study demonstrated different bacterial composition in oral microbiomes of healthy dogs without clinical signs of periodontal disease and their owners. Due to the low numbers of the samples tested, further investigations with an increased number of samples should be performed.
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Affiliation(s)
- Laura Šakarnytė
- Microbiology and Virology Institute, Lithuanian University of Health Sciences, 44307 Kaunas, Lithuania; (L.Š.); (R.Š.)
| | - Rita Šiugždinienė
- Microbiology and Virology Institute, Lithuanian University of Health Sciences, 44307 Kaunas, Lithuania; (L.Š.); (R.Š.)
| | - Judita Žymantienė
- Department of Anatomy and Physiology, Veterinary Academy, Lithuanian University of Health Sciences, 44307 Kaunas, Lithuania;
| | - Modestas Ruzauskas
- Microbiology and Virology Institute, Lithuanian University of Health Sciences, 44307 Kaunas, Lithuania; (L.Š.); (R.Š.)
- Department of Anatomy and Physiology, Veterinary Academy, Lithuanian University of Health Sciences, 44307 Kaunas, Lithuania;
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9
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Flint A, Cooper A, Rao M, Weedmark K, Carrillo C, Tamber S. Targeted metagenomics using bait-capture to detect antibiotic resistance genes in retail meat and seafood. Front Microbiol 2023; 14:1188872. [PMID: 37520363 PMCID: PMC10373929 DOI: 10.3389/fmicb.2023.1188872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 06/28/2023] [Indexed: 08/01/2023] Open
Abstract
Metagenomics analysis of foods has the potential to provide comprehensive data on the presence and prevalence of antimicrobial resistance (AMR) genes in the microbiome of foods. However, AMR genes are generally present in low abundance compared to other bacterial genes in the food microbiome and consequently require multiple rounds of in-depth sequencing for detection. Here, a metagenomics approach, using bait-capture probes targeting antimicrobial resistance and plasmid genes, is used to characterize the resistome and plasmidome of retail beef, chicken, oyster, shrimp, and veal enrichment cultures (n = 15). Compared to total shotgun metagenomics, bait-capture required approximately 40-fold fewer sequence reads to detect twice the number of AMR gene classes, AMR gene families, and plasmid genes across all sample types. For the detection of critically important extended spectrum beta-lactamase (ESBL) genes the bait capture method had a higher overall positivity rate (44%) compared to shotgun metagenomics (26%), and a culture-based method (29%). Overall, the results support the use of bait-capture for the identification of low abundance genes such as AMR genes from food samples.
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Affiliation(s)
- Annika Flint
- Bureau of Microbial Hazards, Health Canada, Sir Frederick Banting Driveway, Ottawa, ON, Canada
| | - Ashley Cooper
- Research and Development, Ottawa Laboratory (Carling), Canadian Food Inspection Agency, Ottawa, ON, Canada
| | - Mary Rao
- Bureau of Microbial Hazards, Health Canada, Sir Frederick Banting Driveway, Ottawa, ON, Canada
| | - Kelly Weedmark
- Bureau of Microbial Hazards, Health Canada, Sir Frederick Banting Driveway, Ottawa, ON, Canada
| | - Catherine Carrillo
- Research and Development, Ottawa Laboratory (Carling), Canadian Food Inspection Agency, Ottawa, ON, Canada
| | - Sandeep Tamber
- Bureau of Microbial Hazards, Health Canada, Sir Frederick Banting Driveway, Ottawa, ON, Canada
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10
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Obe T, Siceloff AT, Crowe MG, Scott HM, Shariat NW. Combined Quantification and Deep Serotyping for Salmonella Risk Profiling in Broiler Flocks. Appl Environ Microbiol 2023; 89:e0203522. [PMID: 36920215 PMCID: PMC10132105 DOI: 10.1128/aem.02035-22] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 02/08/2023] [Indexed: 03/16/2023] Open
Abstract
Despite a reduction of Salmonella contamination on final poultry products, the level of human salmonellosis cases attributed to poultry has remained unchanged over the last few years. There needs to be improved effort to target serovars which may survive antimicrobial interventions and cause illness, as well as to focus on lessening the amount of contamination entering the processing plant. Advances in molecular enumeration approaches allow for the rapid detection and quantification of Salmonella in pre- and postharvest samples, which can be combined with deep serotyping to properly assess the risk affiliated with a poultry flock. In this study, we collected a total of 160 boot sock samples from 20 broiler farms across four different integrators with different antibiotic management programs. Overall, Salmonella was found in 85% (68/80) of the houses, with each farm having at least one Salmonella-positive house. The average Salmonella quantity across all four complexes was 3.6 log10 CFU/sample. Eleven different serovars were identified through deep serotyping, including all three key performance indicators (KPIs; serovars Enteritidis, Infantis, and Typhimurium) defined by the U.S. Department of Agriculture-Food Safety and Inspection Service (USDA-FSIS). There were eight multidrug resistant isolates identified in this study, and seven which were serovar Infantis. We generated risk scores for each flock based on the presence or absence of KPIs, the relative abundance of each serovar as calculated with CRISPR-SeroSeq (serotyping by sequencing the clustered regularly interspaced palindromic repeats), and the quantity of Salmonella organisms detected. The work presented here provides a framework to develop directed processing approaches and highlights the limitations of conventional Salmonella sampling and culturing methods. IMPORTANCE Nearly one in five foodborne Salmonella illnesses are derived from chicken, making it the largest single food category to cause salmonellosis and indicating a need for effective pathogen mitigation. Although industry has successfully reduced Salmonella incidence in poultry products, there has not been a concurrent reduction in human salmonellosis linked to chicken consumption. New efforts are focused on improved control at preharvest, which requires improved Salmonella surveillance. Here, we present a high-resolution surveillance approach that combines quantity and identity of Salmonella in broiler flocks prior to processing which will further support improved Salmonella controls in poultry. We developed a framework for this approach, indicating that it is possible and important to harness deep serotyping and molecular enumeration to inform on-farm management practices and to minimize risk of cross-contamination between flocks at processing. Additionally, this framework could be adapted to Salmonella surveillance in other food animal production systems.
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Affiliation(s)
- Tomi Obe
- Poultry Diagnostic and Research Center, Department of Population Health, College of Veterinary Medicine, University of Georgia, Athens, Georgia, USA
| | - Amy T. Siceloff
- Poultry Diagnostic and Research Center, Department of Population Health, College of Veterinary Medicine, University of Georgia, Athens, Georgia, USA
| | - Megan G. Crowe
- Poultry Diagnostic and Research Center, Department of Population Health, College of Veterinary Medicine, University of Georgia, Athens, Georgia, USA
| | - H. Morgan Scott
- Department of Veterinary Pathobiology, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas, USA
| | - Nikki W. Shariat
- Poultry Diagnostic and Research Center, Department of Population Health, College of Veterinary Medicine, University of Georgia, Athens, Georgia, USA
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11
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Shay JA, Haniford LSE, Cooper A, Carrillo CD, Blais BW, Lau CHF. Exploiting a targeted resistome sequencing approach in assessing antimicrobial resistance in retail foods. ENVIRONMENTAL MICROBIOME 2023; 18:25. [PMID: 36991496 PMCID: PMC10052294 DOI: 10.1186/s40793-023-00482-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 03/15/2023] [Indexed: 06/16/2023]
Abstract
BACKGROUND With the escalating risk of antimicrobial resistance (AMR), there are limited analytical options available that can comprehensively assess the burden of AMR carried by clinical/environmental samples. Food can be a potential source of AMR bacteria for humans, but its significance in driving the clinical spread of AMR remains unclear, largely due to the lack of holistic-yet-sensitive tools for surveillance and evaluation. Metagenomics is a culture-independent approach well suited for uncovering genetic determinants of defined microbial traits, such as AMR, present within unknown bacterial communities. Despite its popularity, the conventional approach of non-selectively sequencing a sample's metagenome (namely, shotgun-metagenomics) has several technical drawbacks that lead to uncertainty about its effectiveness for AMR assessment; for instance, the low discovery rate of resistance-associated genes due to their naturally small genomic footprint within the vast metagenome. Here, we describe the development of a targeted resistome sequencing method and demonstrate its application in the characterization of the AMR gene profile of bacteria associated with several retail foods. RESULT A targeted-metagenomic sequencing workflow using a customized bait-capture system targeting over 4,000 referenced AMR genes and 263 plasmid replicon sequences was validated against both mock and sample-derived bacterial community preparations. Compared to shotgun-metagenomics, the targeted method consistently provided for improved recovery of resistance gene targets with a much-improved target detection efficiency (> 300-fold). Targeted resistome analyses conducted on 36 retail-acquired food samples (fresh sprouts, n = 10; ground meat, n = 26) and their corresponding bacterial enrichment cultures (n = 36) reveals in-depth features regarding the identity and diversity of AMR genes, most of which were otherwise undetected by the whole-metagenome shotgun sequencing method. Furthermore, our findings suggest that foodborne Gammaproteobacteria could be the major reservoir of food-associated AMR genetic determinants, and that the resistome structure of the selected high-risk food commodities are, to a large extent, dictated by microbiome composition. CONCLUSIONS For metagenomic sequencing-based surveillance of AMR, the target-capture method presented herein represents a more sensitive and efficient approach to evaluate the resistome profile of complex food or environmental samples. This study also further implicates retail foods as carriers of diverse resistance-conferring genes indicating a potential impact on the dissemination of AMR.
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Affiliation(s)
- Julie A Shay
- Ottawa Laboratory (Carling), Canadian Food Inspection Agency, Ottawa, ON, Canada
| | - Laura S E Haniford
- Ottawa Laboratory (Carling), Canadian Food Inspection Agency, Ottawa, ON, Canada
| | - Ashley Cooper
- Ottawa Laboratory (Carling), Canadian Food Inspection Agency, Ottawa, ON, Canada
| | - Catherine D Carrillo
- Ottawa Laboratory (Carling), Canadian Food Inspection Agency, Ottawa, ON, Canada
| | - Burton W Blais
- Ottawa Laboratory (Carling), Canadian Food Inspection Agency, Ottawa, ON, Canada
| | - Calvin Ho-Fung Lau
- Ottawa Laboratory (Carling), Canadian Food Inspection Agency, Ottawa, ON, Canada.
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12
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Pinnell LJ, Kuiper G, Huebner KL, Doster E, Parker JK, Alekozai N, Powers JG, Wallen RL, Belk KE, Morley PS. More than an anthropogenic phenomenon: Antimicrobial resistance in ungulates from natural and agricultural environments. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 858:159789. [PMID: 36309273 DOI: 10.1016/j.scitotenv.2022.159789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 10/24/2022] [Accepted: 10/24/2022] [Indexed: 06/16/2023]
Abstract
Widely considered an anthropogenic phenomenon, antimicrobial resistance (AMR) is a naturally occurring mechanism that microorganisms use to gain competitive advantage. AMR represents a significant threat to public health and has generated criticism towards the overuse of antimicrobial drugs. Livestock have been proposed as important reservoirs for AMR accumulation. Here, we show that assemblages of AMR genes in cattle and ungulates from natural environments (Yellowstone and Rocky Mountain National Parks) are all dominated by genes conferring resistance to tetracyclines. However, cattle feces contained higher proportions of erm(A-X) genes conferring resistance to macrolide antibiotics. Medically important AMR genes differed between cattle and natural ungulates, but cumulatively were more predominant in natural soils. Our findings suggest that the commonly described predominance of tetracycline resistance in cattle feces is a natural phenomenon among multiple ungulate species and not solely a result of antimicrobial drug exposure. Yet, the virtual absence of macrolide resistance genes in natural ungulates suggests that macrolide usage in agriculture may enrich these genes in cattle. Our results show that antimicrobial use in agriculture may be promoting a potential reservoir for specific types of AMR (i.e., macrolide resistance) but that a significant proportion of the ungulate resistome appears to have natural origins.
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Affiliation(s)
- Lee J Pinnell
- Veterinary Education, Research, and Outreach Program, Texas A&M University, Canyon, TX 79015, USA
| | - Grace Kuiper
- Colorado State University, Fort Collins, CO 80523, USA
| | | | - Enrique Doster
- Veterinary Education, Research, and Outreach Program, Texas A&M University, Canyon, TX 79015, USA; Colorado State University, Fort Collins, CO 80523, USA
| | | | | | - Jenny G Powers
- Biological Resources Division, National Park Service, Fort Collins, CO 80521, USA
| | - Rick L Wallen
- Yellowstone National Park, National Park Service, Mammoth, WY 82190, USA
| | - Keith E Belk
- Colorado State University, Fort Collins, CO 80523, USA
| | - Paul S Morley
- Veterinary Education, Research, and Outreach Program, Texas A&M University, Canyon, TX 79015, USA.
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13
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Zhang F, Gia A, Chen G, Gong L, Behary J, Hold GL, Zekry A, Tang X, Sun Y, El-Omar E, Jiang XT. Critical Assessment of Whole Genome and Viral Enrichment Shotgun Metagenome on the Characterization of Stool Total Virome in Hepatocellular Carcinoma Patients. Viruses 2022; 15:53. [PMID: 36680094 PMCID: PMC9866815 DOI: 10.3390/v15010053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 12/19/2022] [Accepted: 12/22/2022] [Indexed: 12/28/2022] Open
Abstract
Viruses are the most abundant form of life on earth and play important roles in a broad range of ecosystems. Currently, two methods, whole genome shotgun metagenome (WGSM) and viral-like particle enriched metagenome (VLPM) sequencing, are widely applied to compare viruses in various environments. However, there is no critical assessment of their performance in recovering viruses and biological interpretation in comparative viral metagenomic studies. To fill this gap, we applied the two methods to investigate the stool virome in hepatocellular carcinoma (HCC) patients and healthy controls. Both WGSM and VLPM methods can capture the major diversity patterns of alpha and beta diversities and identify the altered viral profiles in the HCC stool samples compared with healthy controls. Viral signatures identified by both methods showed reductions of Faecalibacterium virus Taranis in HCC patients' stool. Ultra-deep sequencing recovered more viruses in both methods, however, generally, 3 or 5 Gb were sufficient to capture the non-fragmented long viral contigs. More lytic viruses were detected than lysogenetic viruses in both methods, and the VLPM can detect the RNA viruses. Using both methods would identify shared and specific viral signatures and would capture different parts of the total virome.
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Affiliation(s)
- Fan Zhang
- Microbiome Research Centre, St George and Sutherland Clinical School, University of New South Wales, Sydney, NSW 2217, Australia
| | - Andrew Gia
- Microbiome Research Centre, St George and Sutherland Clinical School, University of New South Wales, Sydney, NSW 2217, Australia
| | - Guowei Chen
- Department of Electrical Engineering, City University of Hong Kong, Hong Kong SAR, China
| | - Lan Gong
- Microbiome Research Centre, St George and Sutherland Clinical School, University of New South Wales, Sydney, NSW 2217, Australia
| | - Jason Behary
- Microbiome Research Centre, St George and Sutherland Clinical School, University of New South Wales, Sydney, NSW 2217, Australia
- Department of Gastroenterology, St George Hospital, Sydney, NSW 2217, Australia
| | - Georgina L. Hold
- Microbiome Research Centre, St George and Sutherland Clinical School, University of New South Wales, Sydney, NSW 2217, Australia
| | - Amany Zekry
- Microbiome Research Centre, St George and Sutherland Clinical School, University of New South Wales, Sydney, NSW 2217, Australia
- Department of Gastroenterology, St George Hospital, Sydney, NSW 2217, Australia
| | - Xubo Tang
- Department of Electrical Engineering, City University of Hong Kong, Hong Kong SAR, China
| | - Yanni Sun
- Department of Electrical Engineering, City University of Hong Kong, Hong Kong SAR, China
| | - Emad El-Omar
- Microbiome Research Centre, St George and Sutherland Clinical School, University of New South Wales, Sydney, NSW 2217, Australia
- Department of Gastroenterology, St George Hospital, Sydney, NSW 2217, Australia
| | - Xiao-Tao Jiang
- Microbiome Research Centre, St George and Sutherland Clinical School, University of New South Wales, Sydney, NSW 2217, Australia
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14
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Li Y, Shi X, Zuo Y, Li T, Liu L, Shen Z, Shen J, Zhang R, Wang S. Multiplexed Target Enrichment Enables Efficient and In-Depth Analysis of Antimicrobial Resistome in Metagenomes. Microbiol Spectr 2022; 10:e0229722. [PMID: 36287061 PMCID: PMC9769626 DOI: 10.1128/spectrum.02297-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Accepted: 10/04/2022] [Indexed: 01/06/2023] Open
Abstract
Antibiotic resistance genes (ARGs) pose a serious threat to public health and ecological security in the 21st century. However, the resistome only accounts for a tiny fraction of metagenomic content, which makes it difficult to investigate low-abundance ARGs in various environmental settings. Thus, a highly sensitive, accurate, and comprehensive method is needed to describe ARG profiles in complex metagenomic samples. In this study, we established a high-throughput sequencing method based on targeted amplification, which could simultaneously detect ARGs (n = 251), mobile genetic element genes (n = 8), and metal resistance genes (n = 19) in metagenomes. The performance of amplicon sequencing was compared with traditional metagenomic shotgun sequencing (MetaSeq). A total of 1421 primer pairs were designed, achieving extremely high coverage of target genes. The amplicon sequencing significantly improved the recovery of target ARGs (~9 × 104-fold), with higher sensitivity and diversity, less cost, and computation burden. Furthermore, targeted enrichment allows deep scanning of single nucleotide polymorphisms (SNPs), and elevated SNPs detection was shown in this study. We further performed this approach for 48 environmental samples (37 feces, 20 soils, and 7 sewage) and 16 clinical samples. All samples tested in this study showed high diversity and recovery of targeted genes. Our results demonstrated that the approach could be applied to various metagenomic samples and served as an efficient tool in the surveillance and evolution assessment of ARGs. Access to the resistome using the enrichment method validated in this study enabled the capture of low-abundance resistomes while being less costly and time-consuming, which can greatly advance our understanding of local and global resistome dynamics. IMPORTANCE ARGs, an increasing global threat to human health, can be transferred into health-related microorganisms in the environment by horizontal gene transfer, posing a serious threat to public health. Advancing profiling methods are needed for monitoring and predicting the potential risks of ARGs in metagenomes. Our study described a customized amplicon sequencing assay that could enable a high-throughput, targeted, in-depth analysis of ARGs and detect a low-abundance portion of resistomes. This method could serve as an efficient tool to assess the variation and evolution of specific ARGs in the clinical and natural environment.
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Affiliation(s)
- Yiming Li
- Beijing Key Laboratory of Detection Technology for Animal-Derived Food Safety, College of Veterinary Medicine, China Agricultural University, Beijing, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China
| | - Xiaomin Shi
- Beijing Key Laboratory of Detection Technology for Animal-Derived Food Safety, College of Veterinary Medicine, China Agricultural University, Beijing, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China
| | - Yang Zuo
- Beijing Key Laboratory of Detection Technology for Animal-Derived Food Safety, College of Veterinary Medicine, China Agricultural University, Beijing, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China
| | - Tian Li
- Beijing Key Laboratory of Detection Technology for Animal-Derived Food Safety, College of Veterinary Medicine, China Agricultural University, Beijing, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China
| | - Lu Liu
- Beijing Key Laboratory of Detection Technology for Animal-Derived Food Safety, College of Veterinary Medicine, China Agricultural University, Beijing, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China
| | - Zhangqi Shen
- Beijing Key Laboratory of Detection Technology for Animal-Derived Food Safety, College of Veterinary Medicine, China Agricultural University, Beijing, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China
| | - Jianzhong Shen
- Beijing Key Laboratory of Detection Technology for Animal-Derived Food Safety, College of Veterinary Medicine, China Agricultural University, Beijing, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China
| | - Rong Zhang
- The Second Affiliated Hospital of Zhejiang University, Zhejiang University, Hangzhou, China
| | - Shaolin Wang
- Beijing Key Laboratory of Detection Technology for Animal-Derived Food Safety, College of Veterinary Medicine, China Agricultural University, Beijing, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China
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15
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Doster E, Pinnell LJ, Noyes NR, Parker JK, Anderson CA, Booker CW, Hannon SJ, McAllister TA, Gow SP, Belk KE, Morley PS. Evaluating the effects of antimicrobial drug use on the ecology of antimicrobial resistance and microbial community structure in beef feedlot cattle. Front Microbiol 2022; 13:970358. [PMID: 36583056 PMCID: PMC9792868 DOI: 10.3389/fmicb.2022.970358] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 11/10/2022] [Indexed: 12/14/2022] Open
Abstract
Introduction Use of antimicrobial drugs (AMDs) in food producing animals has received increasing scrutiny because of concerns about antimicrobial resistance (AMR) that might affect consumers. Previously, investigations regarding AMR have focused largely on phenotypes of selected pathogens and indicator bacteria, such as Salmonella enterica or Escherichia coli. However, genes conferring AMR are known to be distributed and shared throughout microbial communities. The objectives of this study were to employ target-enriched metagenomic sequencing and 16S rRNA gene amplicon sequencing to investigate the effects of AMD use, in the context of other management and environmental factors, on the resistome and microbiome in beef feedlot cattle. Methods This study leveraged samples collected during a previous longitudinal study of cattle at beef feedlots in Canada. This included fecal samples collected from randomly selected individual cattle, as well as composite-fecal samples from randomly selected pens of cattle. All AMD use was recorded and characterized across different drug classes using animal defined daily dose (ADD) metrics. Results Overall, fecal resistome composition was dominated by genes conferring resistance to tetracycline and macrolide-lincosamide-streptogramin (MLS) drug classes. The diversity of bacterial phyla was greater early in the feeding period and decreased over time in the feedlot. This decrease in diversity occurred concurrently as the microbiome represented in different individuals and different pens shifted toward a similar composition dominated by Proteobacteria and Firmicutes. Some antimicrobial drug exposures in individuals and groups were associated with explaining a statistically significant proportion of the variance in the resistome, but the amount of variance explained by these important factors was very small (<0.6% variance each), and smaller than associations with other factors measured in this study such as time and feedlot ID. Time in the feedlot was associated with greater changes in the resistome for both individual animals and composite pen-floor samples, although the proportion of the variance associated with this factor was small (2.4% and 1.2%, respectively). Discussion Results of this study are consistent with other investigations showing that, compared to other factors, AMD exposures did not have strong effects on antimicrobial resistance or the fecal microbial ecology of beef cattle.
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Affiliation(s)
- Enrique Doster
- Department of Microbiology, Immunology, & Pathology, Colorado State University, Fort Collins, CO, United States,Veterinary Education, Research, and Outreach Program, Texas A&M University, Canyon, TX, United States
| | - Lee J. Pinnell
- Veterinary Education, Research, and Outreach Program, Texas A&M University, Canyon, TX, United States
| | - Noelle R. Noyes
- Department of Veterinary Population Medicine, University of Minnesota, Minneapolis, MN, United States
| | - Jennifer K. Parker
- Department of Microbiology, Immunology, & Pathology, Colorado State University, Fort Collins, CO, United States
| | - Cameron A. Anderson
- Department of Microbiology, Immunology, & Pathology, Colorado State University, Fort Collins, CO, United States
| | | | | | | | - Sheryl P. Gow
- Public Health Agency of Canada, Saskatoon, SK, Canada
| | - Keith E. Belk
- Department of Microbiology, Immunology, & Pathology, Colorado State University, Fort Collins, CO, United States
| | - Paul S. Morley
- Veterinary Education, Research, and Outreach Program, Texas A&M University, Canyon, TX, United States,*Correspondence: Paul S. Morley,
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16
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Slizovskiy IB, Oliva M, Settle JK, Zyskina LV, Prosperi M, Boucher C, Noyes NR. Target-enriched long-read sequencing (TELSeq) contextualizes antimicrobial resistance genes in metagenomes. MICROBIOME 2022; 10:185. [PMID: 36324140 PMCID: PMC9628182 DOI: 10.1186/s40168-022-01368-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 09/02/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Metagenomic data can be used to profile high-importance genes within microbiomes. However, current metagenomic workflows produce data that suffer from low sensitivity and an inability to accurately reconstruct partial or full genomes, particularly those in low abundance. These limitations preclude colocalization analysis, i.e., characterizing the genomic context of genes and functions within a metagenomic sample. Genomic context is especially crucial for functions associated with horizontal gene transfer (HGT) via mobile genetic elements (MGEs), for example antimicrobial resistance (AMR). To overcome this current limitation of metagenomics, we present a method for comprehensive and accurate reconstruction of antimicrobial resistance genes (ARGs) and MGEs from metagenomic DNA, termed target-enriched long-read sequencing (TELSeq). RESULTS Using technical replicates of diverse sample types, we compared TELSeq performance to that of non-enriched PacBio and short-read Illumina sequencing. TELSeq achieved much higher ARG recovery (>1,000-fold) and sensitivity than the other methods across diverse metagenomes, revealing an extensive resistome profile comprising many low-abundance ARGs, including some with public health importance. Using the long reads generated by TELSeq, we identified numerous MGEs and cargo genes flanking the low-abundance ARGs, indicating that these ARGs could be transferred across bacterial taxa via HGT. CONCLUSIONS TELSeq can provide a nuanced view of the genomic context of microbial resistomes and thus has wide-ranging applications in public, animal, and human health, as well as environmental surveillance and monitoring of AMR. Thus, this technique represents a fundamental advancement for microbiome research and application. Video abstract.
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Affiliation(s)
- Ilya B Slizovskiy
- Food-Centric Corridor, Infectious Disease Laboratory, Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, USA
| | - Marco Oliva
- Department of Computer and Information Science and Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL, USA
| | - Jonathen K Settle
- Department of Computer and Information Science and Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL, USA
| | - Lidiya V Zyskina
- Program in Human-Computer Interaction, College of Information Studies, University of Maryland, College Park, MD, USA
| | - Mattia Prosperi
- Data Intelligence Systems Lab, Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA
| | - Christina Boucher
- Department of Computer and Information Science and Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL, USA
| | - Noelle R Noyes
- Food-Centric Corridor, Infectious Disease Laboratory, Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, USA.
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17
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Gaire TN, Odland C, Zhang B, Ray T, Doster E, Nerem J, Dee S, Davies P, Noyes N. The impacts of viral infection and subsequent antimicrobials on the microbiome-resistome of growing pigs. MICROBIOME 2022; 10:118. [PMID: 35922873 PMCID: PMC9351240 DOI: 10.1186/s40168-022-01312-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 06/21/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Antimicrobials are used in food-producing animals for purposes of preventing, controlling, and/or treating infections. In swine, a major driver of antimicrobial use is porcine reproductive and respiratory syndrome (PRRS), which is caused by a virus that predisposes infected animals to secondary bacterial infections. Numerous antimicrobial protocols are used to treat PRRS, but we have little insight into how these treatment schemes impact antimicrobial resistance (AMR) dynamics within the fecal microbiome of commercial swine. The aim of this study was to determine whether different PRRS-relevant antimicrobial treatment protocols were associated with differences in the fecal microbiome and resistome of growing pigs. To accomplish this, we used a metagenomics approach to characterize and compare the longitudinal wean-to-market resistome and microbiome of pigs challenged with PRRS virus and then exposed to different antimicrobial treatments, and a group of control pigs not challenged with PRRS virus and having minimal antimicrobial exposure. Genomic DNA was extracted from pen-level composite fecal samples from each treatment group and subjected to metagenomic sequencing and microbiome-resistome bioinformatic and statistical analysis. Microbiome-resistome profiles were compared over time and between treatment groups. RESULTS Fecal microbiome and resistome compositions both changed significantly over time, with a dramatic and stereotypic shift between weaning and 9 days post-weaning (dpw). Antimicrobial resistance gene (ARG) richness and diversity were significantly higher at earlier time points, while microbiome richness and diversity were significantly lower. The post-weaning shift was characterized by transition from a Bacteroides-dominated enterotype to Lactobacillus- and Streptococcus-dominated enterotypes. Both the microbiome and resistome stabilized by 44 dpw, at which point the trajectory of microbiome-resistome maturation began to diverge slightly between the treatment groups, potentially due to physical clustering of the pigs. Challenge with PRRS virus seemed to correspond to the re-appearance of many very rare and low-abundance ARGs within the feces of challenged pigs. Despite very different antimicrobial exposures after challenge with PRRS virus, resistome composition remained largely similar between the treatment groups. Differences in ARG abundance between the groups were mostly driven by temporal changes in abundance that occurred prior to antimicrobial exposures, with the exception of ermG, which increased in the feces of treated pigs, and was significantly more abundant in the feces of these pigs compared to the pigs that did not receive post-PRRS antimicrobials. CONCLUSIONS The fecal microbiome-resistome of growing pigs exhibited a stereotypic trajectory driven largely by weaning and physiologic aging of the pigs. Events such as viral illness, antimicrobial exposures, and physical grouping of the pigs exerted significant yet relatively minor influence over this trajectory. Therefore, the AMR profile of market-age pigs is the culmination of the life history of the individual pigs and the populations to which they belong. Disease status alone may be a significant driver of AMR in market-age pigs, and understanding the interaction between disease processes and antimicrobial exposures on the swine microbiome-resistome is crucial to developing effective, robust, and reproducible interventions to control AMR. Video Abstract.
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Affiliation(s)
- Tara N Gaire
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, Minnesota, USA
| | - Carissa Odland
- Pipestone Veterinary Services, Pipestone, Minnesota, USA
| | - Bingzhou Zhang
- State Key Laboratory of Agricultural Microbiology, College of Animal Sciences and Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China
| | - Tui Ray
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, Minnesota, USA
| | - Enrique Doster
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, Minnesota, USA
| | - Joel Nerem
- Pipestone Applied Research, Pipestone, Minnesota, USA
| | - Scott Dee
- Pipestone Applied Research, Pipestone, Minnesota, USA
| | - Peter Davies
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, Minnesota, USA
| | - Noelle Noyes
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, Minnesota, USA.
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18
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Alanko JN, Slizovskiy IB, Lokshtanov D, Gagie T, Noyes NR, Boucher C. Syotti: scalable bait design for DNA enrichment. Bioinformatics 2022; 38:i177-i184. [PMID: 35758776 PMCID: PMC9235489 DOI: 10.1093/bioinformatics/btac226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION Bait enrichment is a protocol that is becoming increasingly ubiquitous as it has been shown to successfully amplify regions of interest in metagenomic samples. In this method, a set of synthetic probes ('baits') are designed, manufactured and applied to fragmented metagenomic DNA. The probes bind to the fragmented DNA and any unbound DNA is rinsed away, leaving the bound fragments to be amplified for sequencing. Metsky et al. demonstrated that bait-enrichment is capable of detecting a large number of human viral pathogens within metagenomic samples. RESULTS We formalize the problem of designing baits by defining the Minimum Bait Cover problem, show that the problem is NP-hard even under very restrictive assumptions, and design an efficient heuristic that takes advantage of succinct data structures. We refer to our method as Syotti. The running time of Syotti shows linear scaling in practice, running at least an order of magnitude faster than state-of-the-art methods, including the method of Metsky et al. At the same time, our method produces bait sets that are smaller than the ones produced by the competing methods, while also leaving fewer positions uncovered. Lastly, we show that Syotti requires only 25 min to design baits for a dataset comprised of 3 billion nucleotides from 1000 related bacterial substrains, whereas the method of Metsky et al. shows clearly super-linear running time and fails to process even a subset of 17% of the data in 72 h. AVAILABILITY AND IMPLEMENTATION https://github.com/jnalanko/syotti. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Jarno N Alanko
- Department of Computer Science, University of Helsinki, Helsinki, Finland
- Faculty of Computer Science, Dalhousie University, Halifax, Canada
| | - Ilya B Slizovskiy
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN, USA
| | - Daniel Lokshtanov
- Department of Computer Science, University of California, Santa Barbara, CA, USA
| | - Travis Gagie
- Faculty of Computer Science, Dalhousie University, Halifax, Canada
| | - Noelle R Noyes
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN, USA
| | - Christina Boucher
- Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA
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19
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Kormos D, Lin K, Pruden A, Marr LC. Critical review of antibiotic resistance genes in the atmosphere. ENVIRONMENTAL SCIENCE. PROCESSES & IMPACTS 2022; 24:870-883. [PMID: 35638569 DOI: 10.1039/d2em00091a] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
We conducted a critical review to establish what is known about the sources, characteristics, and dissemination of ARGs in the atmosphere. We identified 52 papers that reported direct measurements of bacterial ARGs in air samples and met other inclusion criteria. The settings of the studies fell into the following categories: urban, rural, hospital, industrial, wastewater treatment plants (WWTPs), composting and landfill sites, and indoor environments. Certain genes were commonly studied and generally abundant: sul1, intI1, β-lactam ARGs, and tetracycline ARGs. Abundances of total ARGs varied by season and setting, with air in urban areas having higher ARG abundance than rural areas during the summer and vice versa during the winter. There was greater consistency in the types and abundances of ARGs throughout the seasons in urban areas. Human activity within indoor environments was also linked to increased ARG content (abundance, diversity, and concentration) in the air. Several studies found that human exposure to ARGs through inhalation was comparable to exposure through drinking water or ingesting soil. Detection of ARGs in air is a developing field, and differences in sampling and analysis methods reflect the many possible approaches to studying ARGs in air and make direct comparisons between studies difficult. Methodologies need to be standardized to facilitate identification of the dominant ARGs in the air, determine their major sources, and quantify the role of atmospheric transport in dissemination of ARGs in the environment. With such knowledge we can develop better policies and guidelines to limit the spread of antimicrobial resistance.
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Affiliation(s)
- David Kormos
- Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA.
| | - Kaisen Lin
- Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA.
| | - Amy Pruden
- Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA.
| | - Linsey C Marr
- Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA.
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20
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Diversity of Antibiotic Resistance genes and Transfer Elements-Quantitative Monitoring (DARTE-QM): a method for detection of antimicrobial resistance in environmental samples. Commun Biol 2022; 5:216. [PMID: 35301418 PMCID: PMC8931014 DOI: 10.1038/s42003-022-03155-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Accepted: 02/02/2022] [Indexed: 12/01/2022] Open
Abstract
Effective monitoring of antibiotic resistance genes and their dissemination in environmental ecosystems has been hindered by the cost and efficiency of methods available for the task. We developed the Diversity of Antibiotic Resistance genes and Transfer Elements-Quantitative Monitoring (DARTE-QM), a method implementing TruSeq high-throughput sequencing to simultaneously sequence thousands of antibiotic resistant gene targets representing a full-spectrum of antibiotic resistance classes common to environmental systems. In this study, we demonstrated DARTE-QM by screening 662 antibiotic resistance genes within complex environmental samples originated from manure, soil, and livestock feces, in addition to a mock-community reference to assess sensitivity and specificity. DARTE-QM offers a new approach to studying antibiotic resistance in environmental microbiomes, showing advantages in efficiency and the ability to scale for many samples. This method provides a means of data acquisition that will alleviate some of the obstacles that many researchers in this area currently face. Smith et al. present DARTE-QM, a highthroughput sequencing method for screening environmental DNA samples for antibiotic resistance genes on a broad scale. This method is demonstrated as effective on soil, manure and livestock fecal samples, as well as a synthetic mock-community reference.
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21
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Weinroth MD, Thomas KM, Doster E, Vikram A, Schmidt JW, Arthur TM, Wheeler TL, Parker JK, Hanes AS, Alekoza N, Wolfe C, Metcalf JL, Morley PS, Belk KE. Resistomes and microbiome of meat trimmings and colon content from culled cows raised in conventional and organic production systems. Anim Microbiome 2022; 4:21. [PMID: 35272712 PMCID: PMC8908682 DOI: 10.1186/s42523-022-00166-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 02/04/2022] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND The potential to distribute bacteria resistant to antimicrobial drugs in the meat supply is a public health concern. Market cows make up a fifth of the U.S. beef produced but little is known about the entire population of bacteria (the microbiome) and entirety of all resistance genes (the resistome) that are found in this population. The objective of this study was to characterize and compare the resistomes and microbiome of beef, dairy, and organic dairy market cows at slaughter. METHODS Fifty-four (N = 54) composite samples of both colon content and meat trimmings rinsate samples were collected over six visits to two harvest facilities from cows raised in three different production systems: conventional beef, conventional dairy, and organic dairy (n = 3 samples per visit per production system). Metagenomic DNA obtained from samples were analyzed using target-enriched sequencing (resistome) and 16S rRNA gene sequencing (microbiome). RESULTS All colon content samples had at least one identifiable antimicrobial resistance gene (ARG), while 21 of the 54 meat trimmings samples harbored at least one identifiable ARGs. Tetracycline ARGs were the most abundant class in both colon content and carcass meat trimmings. The resistome found on carcass meat trimmings was not significantly different by production system (P = 0.84, R2 = 0.00) or harvest facility (P = 0.10, R2 = 0.09). However, the resistome of colon content differed (P = 0.01; R2 = 0.05) among production systems, but not among the harvest facilities (P = 0.41; R2 = 0.00). Amplicon sequencing revealed differences (P < 0.05) in microbial populations in both meat trimmings and colon content between harvest facilities but not production systems (P > 0.05). CONCLUSIONS These data provide a baseline characterization of an important segment of the beef industry and highlight the effect that the production system where cattle are raised and the harvest facilities where an animal is processed can impact associated microbiome and resistomes.
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Affiliation(s)
- Margaret D Weinroth
- Department of Animal Sciences, Colorado State University, Fort Collins, CO, USA
- U.S. Department of Agriculture, Agricultural Research Service, U.S. National Poultry Research Center, Athens, GA, USA
| | - Kevin M Thomas
- Department of Animal Sciences, Colorado State University, Fort Collins, CO, USA
| | - Enrique Doster
- Department of Microbiology Immunology and Pathology, Colorado State University, Fort Collins, CO, USA
| | - Amit Vikram
- U.S. Department of Agriculture, Agricultural Research Service, Roman L. Hruska U.S. Meat Animal Research Center, Clay Center, NE, USA
- Intralytix, Columbia, MD, 21046, USA
| | - John W Schmidt
- U.S. Department of Agriculture, Agricultural Research Service, Roman L. Hruska U.S. Meat Animal Research Center, Clay Center, NE, USA
| | - Terrance M Arthur
- U.S. Department of Agriculture, Agricultural Research Service, Roman L. Hruska U.S. Meat Animal Research Center, Clay Center, NE, USA
| | - Tommy L Wheeler
- U.S. Department of Agriculture, Agricultural Research Service, Roman L. Hruska U.S. Meat Animal Research Center, Clay Center, NE, USA
| | - Jennifer K Parker
- Department of Clinical Sciences, Colorado State University, Fort Collins, CO, USA
| | - Ayanna S Hanes
- Department of Clinical Sciences, Colorado State University, Fort Collins, CO, USA
| | - Najla Alekoza
- Department of Clinical Sciences, Colorado State University, Fort Collins, CO, USA
| | - Cory Wolfe
- Department of Clinical Sciences, Colorado State University, Fort Collins, CO, USA
| | - Jessica L Metcalf
- Department of Animal Sciences, Colorado State University, Fort Collins, CO, USA
| | - Paul S Morley
- Veterinary Education, Research, and Outreach Program, Texas A&M University and West Texas A&M University, Canyon, TX, 79105, USA.
| | - Keith E Belk
- Department of Animal Sciences, Colorado State University, Fort Collins, CO, USA
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22
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Vasquez A, Nydam D, Foditsch C, Warnick L, Wolfe C, Doster E, Morley PS. Characterization and comparison of the microbiomes and resistomes of colostrum from selectively treated dry cows. J Dairy Sci 2021; 105:637-653. [PMID: 34763917 DOI: 10.3168/jds.2021-20675] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 09/16/2021] [Indexed: 12/23/2022]
Abstract
Professionals in animal agriculture promote prudent use of antimicrobials to address public and animal health concerns, such as reduction of antimicrobial residues and antimicrobial resistance (AMR) in products. Few studies evaluate the effect of selective dry-cow therapy on preservation of the milk microbiome or the profile of AMR genes (the resistome) present at freshening. Our objectives were to characterize and compare the microbiomes and resistomes in the colostrum of cows with low somatic cell count that were treated or not treated with intramammary cephapirin benzathine at dry-off. From a larger parent study, cows on a New York dairy farm eligible for dry-off and with histories of somatic cell counts ≤200,000 cells/mL were enrolled to this study (n = 307). Cows were randomly assigned to receive an intramammary antimicrobial and external teat sealant (ABXTS) or sealant only (TS) at dry-off. Composite colostrum samples taken within 4 h of freshening, and quarter milk samples taken at 1 to 7 d in milk were subjected to aerobic culture. The DNA extraction was performed on colostrum from cows with culture-negative samples (ABXTS = 43; TS = 33). The DNA from cows of the same treatment group and parity were pooled (26 pools; ABXTS = 12; TS = 14) for 16S rRNA metagenomic sequencing. Separately, the resistome was captured using a custom RNA bait library for target-enriched sequencing. Sequencing reads were aligned to taxonomic and AMR databases to characterize the microbiome and resistome, respectively. The R statistical program was used to tabulate abundances and to analyze differences in diversity measures and in composition between treatment groups. In the microbiome, the most abundant phyla were Firmicutes (68%), Proteobacteria (23%), Actinobacteria (4%), and Bacteroidetes (3%). Shannon and richness diversity means were 0.93 and 14.7 for ABXTS and 0.94 and 13.1 for TS, respectively. Using analysis of similarities (ANOSIM), overall microbiome composition was found to be similar between treatment groups at the phylum (ANOSIM R = 0.005), class (ANOSIM R = 0.04), and order (ANOSIM R = -0.04) levels. In the resistome, we identified AMR gene accessions associated with 14 unique mechanisms of resistance across 9 different drug classes in 14 samples (TS = 9, ABXTS = 5). The majority of reads aligned to gene accessions that confer resistance to aminoglycoside (TS = ABXTS each 35% abundance), tetracycline (TS = 22%, ABXTS = 54%), and β-lactam classes (TS = 15%, ABXTS = 12%). Shannon diversity means for AMR class and mechanism, respectively, were 0.66 and 0.69 for TS and 0.19 and 0.19 for ABXTS. Resistome richness diversity means for class and mechanism were 3.1 and 3.4 for TS and 1.4 and 1.4 for ABXTS. Finally, resistome composition was similar between groups at the class (ANOSIM R = -0.20) and mechanism levels (ANOSIM R = 0.01). Although no critical differences were found between treatment groups regarding their microbiome or resistome composition in this study, a larger sample size, deeper sequencing, and additional methodology is needed to identify more subtle differences, such as between lower-abundance features.
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Affiliation(s)
- Amy Vasquez
- Department of Population Medicine, Cornell College of Veterinary Medicine, Ithaca, NY 14853.
| | - Daryl Nydam
- Department of Population Medicine, Cornell College of Veterinary Medicine, Ithaca, NY 14853
| | - Carla Foditsch
- Department of Population Medicine, Cornell College of Veterinary Medicine, Ithaca, NY 14853
| | - Lorin Warnick
- Department of Population Medicine, Cornell College of Veterinary Medicine, Ithaca, NY 14853
| | - Cory Wolfe
- Veterinary Education, Research, and Outreach Program, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, Canyon 79015
| | - Enrique Doster
- Veterinary Education, Research, and Outreach Program, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, Canyon 79015; Department of Microbiology, Immunology, and Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins 80521
| | - Paul S Morley
- Veterinary Education, Research, and Outreach Program, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, Canyon 79015
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23
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Wang Y, Zhou J, Peng H, Ma J, Li H, Li L, Li T, Fang Z, Ma A, Fu L. High-Throughput Identification of Allergens in a Food System via Hybridization Probe Cluster-Targeted Next-Generation Sequencing. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2021; 69:11992-12001. [PMID: 34498855 DOI: 10.1021/acs.jafc.1c03595] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Food allergies (FAs) are a crucial public health problem and a severe food safety issue, resulting in an urgent need for an accurate method to detect all of the hidden allergens that exist in food systems. Current methods for detecting allergens typically utilize ELISA, PCR, or LC-MS, which are suitable for the confirmatory analysis of allergens from ingredients rather than unintended contaminants. In this study, we demonstrate a hybridization probe cluster-targeted next-generation sequencing (HPC-NGS) platform for high-throughput screening of potential allergens in food systems. The HPC-NGS successfully captured target DNA fragments and identified 19 allergenic ingredients in a complex food system. Additionally, the HPC-NGS provided expected allergenic species matching rates of 94.24-100% in single food materials and 99.87-99.98% in processed food products. Thus, HPC-NGS enables the accurate characterization of allergenic ingredients and unintended allergenic contaminants in foods. Our results provide new perspectives on the use of HPC-NGS in the accuracy of high-throughput detection technologies for allergens imposed by the complex matrix effect.
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Affiliation(s)
- Yanbo Wang
- Food Safety Key Laboratory of Zhejiang Province, School of Food Science and Biotechnology, Zhejiang Gongshang University, 18 Xue Zheng Street, Hangzhou 310018, Zhejiang, P. R. China
| | - Jinru Zhou
- Food Safety Key Laboratory of Zhejiang Province, School of Food Science and Biotechnology, Zhejiang Gongshang University, 18 Xue Zheng Street, Hangzhou 310018, Zhejiang, P. R. China
| | - Hai Peng
- Institute for Systems Biology, Jianghan University, Wuhan 430056, Hubei, P. R. China
| | - Junjie Ma
- Food Safety Key Laboratory of Zhejiang Province, School of Food Science and Biotechnology, Zhejiang Gongshang University, 18 Xue Zheng Street, Hangzhou 310018, Zhejiang, P. R. China
| | - Huan Li
- Food Safety Key Laboratory of Zhejiang Province, School of Food Science and Biotechnology, Zhejiang Gongshang University, 18 Xue Zheng Street, Hangzhou 310018, Zhejiang, P. R. China
| | - Lun Li
- Institute for Systems Biology, Jianghan University, Wuhan 430056, Hubei, P. R. China
| | - Tiantian Li
- Institute for Systems Biology, Jianghan University, Wuhan 430056, Hubei, P. R. China
| | - Zhiwei Fang
- Institute for Systems Biology, Jianghan University, Wuhan 430056, Hubei, P. R. China
| | - Aijin Ma
- College of Food and Health, Beijing Technology and Business University, Beijing 100048, P. R. China
| | - Linglin Fu
- Food Safety Key Laboratory of Zhejiang Province, School of Food Science and Biotechnology, Zhejiang Gongshang University, 18 Xue Zheng Street, Hangzhou 310018, Zhejiang, P. R. China
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24
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Beaudry MS, Thomas JC, Baptista RP, Sullivan AH, Norfolk W, Devault A, Enk J, Kieran TJ, Rhodes OE, Perry-Dow KA, Rose LJ, Bayona-Vásquez NJ, Oladeinde A, Lipp EK, Sanchez S, Glenn TC. Escaping the fate of Sisyphus: assessing resistome hybridization baits for antimicrobial resistance gene capture. Environ Microbiol 2021; 23:7523-7537. [PMID: 34519156 DOI: 10.1111/1462-2920.15767] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 09/03/2021] [Accepted: 09/07/2021] [Indexed: 11/30/2022]
Abstract
Finding, characterizing and monitoring reservoirs for antimicrobial resistance (AMR) is vital to protecting public health. Hybridization capture baits are an accurate, sensitive and cost-effective technique used to enrich and characterize DNA sequences of interest, including antimicrobial resistance genes (ARGs), in complex environmental samples. We demonstrate the continued utility of a set of 19 933 hybridization capture baits designed from the Comprehensive Antibiotic Resistance Database (CARD)v1.1.2 and Pathogenicity Island Database (PAIDB)v2.0, targeting 3565 unique nucleotide sequences that confer resistance. We demonstrate the efficiency of our bait set on a custom-made resistance mock community and complex environmental samples to increase the proportion of on-target reads as much as >200-fold. However, keeping pace with newly discovered ARGs poses a challenge when studying AMR, because novel ARGs are continually being identified and would not be included in bait sets designed prior to discovery. We provide imperative information on how our bait set performs against CARDv3.3.1, as well as a generalizable approach for deciding when and how to update hybridization capture bait sets. This research encapsulates the full life cycle of baits for hybridization capture of the resistome from design and validation (both in silico and in vitro) to utilization and forecasting updates and retirement.
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Affiliation(s)
- Megan S Beaudry
- Department of Environmental Health Science, University of Georgia, Athens, GA, 30602, USA
| | - Jesse C Thomas
- Department of Environmental Health Science, University of Georgia, Athens, GA, 30602, USA.,Savannah River Ecology Laboratory, University of Georgia, Aiken, SC, 29808, USA
| | - Rodrigo P Baptista
- Institute of Bioinformatics, University of Georgia, Athens, GA, 30602, USA.,Center for Tropical and Emerging Diseases, University of Georgia, Athens, GA, 30602, USA
| | - Amanda H Sullivan
- Department of Environmental Health Science, University of Georgia, Athens, GA, 30602, USA.,Institute of Bioinformatics, University of Georgia, Athens, GA, 30602, USA
| | - William Norfolk
- Department of Environmental Health Science, University of Georgia, Athens, GA, 30602, USA
| | - Alison Devault
- Daicel Arbor Biosciences, 5840 Interface Dr., Suite 101, Ann Arbor, MI, 48103, USA
| | - Jacob Enk
- Daicel Arbor Biosciences, 5840 Interface Dr., Suite 101, Ann Arbor, MI, 48103, USA
| | - Troy J Kieran
- Department of Environmental Health Science, University of Georgia, Athens, GA, 30602, USA
| | - Olin E Rhodes
- Savannah River Ecology Laboratory, University of Georgia, Aiken, SC, 29808, USA.,Odum School of Ecology, University of Georgia, Athens, GA, 30602, USA
| | - K Allison Perry-Dow
- Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Laura J Rose
- Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Natalia J Bayona-Vásquez
- Department of Environmental Health Science, University of Georgia, Athens, GA, 30602, USA.,Institute of Bioinformatics, University of Georgia, Athens, GA, 30602, USA.,Division of Natural Science and Mathematics, Oxford College, Emory University, Oxford, GA, 30054, USA
| | - Adelumola Oladeinde
- Bacterial Epidemiology and Antimicrobial Resistance Research Unit, U.S. National Poultry Research Center, USDA Agricultural Research Service, Athens, GA, 30605, USA
| | - Erin K Lipp
- Department of Environmental Health Science, University of Georgia, Athens, GA, 30602, USA
| | - Susan Sanchez
- Department of Infectious Diseases, University of Georgia, Athens, GA, 30602, USA
| | - Travis C Glenn
- Department of Environmental Health Science, University of Georgia, Athens, GA, 30602, USA.,Institute of Bioinformatics, University of Georgia, Athens, GA, 30602, USA
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25
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Warder LMC, Doster E, Parker JK, Morley PS, McClure JT, Heider LC, Sánchez J. Characterization of the microbiota and resistome of bulk tank milk samples from Prince Edward Island dairy farms. J Dairy Sci 2021; 104:11082-11090. [PMID: 34334208 DOI: 10.3168/jds.2020-19995] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 06/07/2021] [Indexed: 01/04/2023]
Abstract
Bulk tank milk (BTM) is regularly used for surveillance on dairy farms for disease conditions such as mastitis and Johne's disease. In this study, we used 16S rRNA sequencing and bait-capture enrichment to characterize the microbiota and resistome of BTM, and investigate potential differences between the cream or pellet fractions. A total of 12 BTM samples were taken from 12 Prince Edward Island dairy farms, in Atlantic Canada, in duplicates. The DNA was analyzed by high-throughput sequencing of the 16S rRNA gene and a suite of antimicrobial resistance (AMR) genes. Target-capture enrichment of AMR genes was conducted before shotgun sequencing. The bioinformatics pipelines QIIME 2 and AMR++ were used for microbiota and resistome analysis, respectively. Differences between microbiotae were evaluated qualitatively with nonmetric multidimensional scaling and quantitatively with permutational ANOVA of UniFrac distances. A total of 47 phyla were present across the BTM samples. Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria were the most abundant phyla. At the genus level, Corynebacterium, Acinetobacter, Lactobacillus, and Turicibacter were the most abundant. There was no significant difference in the Faith's phylogenetic diversity between the cream and pellet fraction. Faith's phylogenetic diversity differed marginally by stall type. There were 10,217 hits across 80 unique AMR genes, with tetracycline resistance being the most common class.
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Affiliation(s)
- Landon M C Warder
- Department of Health Management, Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, Prince Edward Island, Canada C1A 4P3.
| | - Enrique Doster
- Veterinary Education, Research, and Outreach (VERO) Program, Texas A&M University and West Texas A&M University, Canyon 79015; Department of Microbiology, Immunology and Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins 80523
| | - Jennifer K Parker
- Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins 80523
| | - Paul S Morley
- Veterinary Education, Research, and Outreach (VERO) Program, Texas A&M University and West Texas A&M University, Canyon 79015
| | - J T McClure
- Department of Health Management, Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, Prince Edward Island, Canada C1A 4P3
| | - Luke C Heider
- Department of Health Management, Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, Prince Edward Island, Canada C1A 4P3
| | - Javier Sánchez
- Department of Health Management, Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, Prince Edward Island, Canada C1A 4P3
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26
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Gustafsson J, Robinson J, Nielsen J, Pachter L. BUTTERFLY: addressing the pooled amplification paradox with unique molecular identifiers in single-cell RNA-seq. Genome Biol 2021; 22:174. [PMID: 34103073 PMCID: PMC8188791 DOI: 10.1186/s13059-021-02386-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Accepted: 05/21/2021] [Indexed: 11/30/2022] Open
Abstract
The incorporation of unique molecular identifiers (UMIs) in single-cell RNA-seq assays makes possible the identification of duplicated molecules, thereby facilitating the counting of distinct molecules from sequenced reads. However, we show that the naïve removal of duplicates can lead to a bias due to a "pooled amplification paradox," and we propose an improved quantification method based on unseen species modeling. Our correction called BUTTERFLY uses a zero truncated negative binomial estimator implemented in the kallisto bustools workflow. We demonstrate its efficacy across cell types and genes and show that in some cases it can invert the relative abundance of genes.
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Affiliation(s)
- Johan Gustafsson
- Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, Gothenburg, Sweden
- Wallenberg Center for Protein Research, Chalmers University of Technology, Kemivägen 10, Gothenburg, Sweden
| | - Jonathan Robinson
- Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, Gothenburg, Sweden
- Wallenberg Center for Protein Research, Chalmers University of Technology, Kemivägen 10, Gothenburg, Sweden
- Department of Biology and Biological Engineering, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Chalmers University of Technology, Kemivägen 10, SE-41258, Gothenburg, Sweden
| | - Jens Nielsen
- Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, Gothenburg, Sweden.
- Wallenberg Center for Protein Research, Chalmers University of Technology, Kemivägen 10, Gothenburg, Sweden.
- BioInnovation Institute, Ole Maaløes Vej 3, DK2200, Copenhagen N, Denmark.
| | - Lior Pachter
- Division of Biology and Biological Engineering & Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, USA.
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27
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Mangioni D, Alagna L, Gori A, Bandera A. Fecal Microbiota Transplant: Keep Calm and Carry On, Learning From Experience. Clin Infect Dis 2021; 72:1296-1297. [PMID: 32572461 DOI: 10.1093/cid/ciaa846] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Affiliation(s)
- Davide Mangioni
- Infectious Diseases Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Centre for Multidisciplinary Research in Health Science (MACH), University of Milan, Milan, Italy.,Department of Medical Biotechnology and Translational Medicine, University of Milan, Milan, Italy
| | - Laura Alagna
- Infectious Diseases Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Centre for Multidisciplinary Research in Health Science (MACH), University of Milan, Milan, Italy
| | - Andrea Gori
- Infectious Diseases Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Centre for Multidisciplinary Research in Health Science (MACH), University of Milan, Milan, Italy.,Department of Pathophysiology and Transplantation, School of Medicine and Surgery, University of Milan, Milan, Italy.,Centre for Multidisciplinary Research in Health Science (MACH), University of Milan, Milan, Italy
| | - Alessandra Bandera
- Infectious Diseases Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Centre for Multidisciplinary Research in Health Science (MACH), University of Milan, Milan, Italy.,Department of Pathophysiology and Transplantation, School of Medicine and Surgery, University of Milan, Milan, Italy.,Centre for Multidisciplinary Research in Health Science (MACH), University of Milan, Milan, Italy
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Pérez-Garza J, Franco-Frías E, García-Heredia A, García S, Leon JS, Jaykus LA, Heredia N. The Cantaloupe Farm Environment Has a Diverse Genetic Pool of Antibiotic-Resistance and Virulence Genes. Foodborne Pathog Dis 2021; 18:469-476. [PMID: 33900863 DOI: 10.1089/fpd.2020.2900] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Cantaloupes contaminated with pathogens have led to many high-profile outbreaks and illnesses. Since bacterial virulence genes (VGs) can act in tandem with antibiotic-resistance and mobile genetic elements, there is a need to evaluate these gene reservoirs in fresh produce, such as cantaloupes. The goal of this study was to assess the distribution of antibiotic-resistance, virulence, and mobile genetic elements genes (MGEGs) in cantaloupe farm environments. A total of 200 samples from cantaloupe melons (n = 99), farm workers' hands (n = 66), and production water (n = 35) were collected in México. Each sample was assayed for the presence of 14 antibiotic-resistance genes, 15 VGs, and 5 MGEGs by polymerase chain reaction. Our results indicated that tetracycline (tetA and tetB) (18% of cantaloupe, 45% of hand samples) and sulfonamide (sul1) (30% of cantaloupe, 71% of hand samples) resistance genes were frequently detected. The colistin resistance gene (mcr1) was detected in 10% of cantaloupe and 23% of farm workers' hands. Among VGs, Salmonella genes invA and spiA were the most abundant. There was a significantly higher likelihood of detecting antibiotic-resistance, virulence, and MGEGs on hands compared with water samples. These results demonstrate a diverse pool of antibiotic-resistance and VGs in cantaloupe production.
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Affiliation(s)
- Janeth Pérez-Garza
- Laboratorio de Bioquímica y Genética de Microorganismos, Departamento de Microbiologia e Inmunología, Facultad de Ciencias Biológicas, Universidad Autónoma de Nuevo León, San Nicolas de los Garza, México
| | - Eduardo Franco-Frías
- Laboratorio de Bioquímica y Genética de Microorganismos, Departamento de Microbiologia e Inmunología, Facultad de Ciencias Biológicas, Universidad Autónoma de Nuevo León, San Nicolas de los Garza, México
| | - Alam García-Heredia
- Molecular and Cellular Biology Graduate Program, University of Massachusetts, Amherst, Massachusetts, USA
| | - Santos García
- Laboratorio de Bioquímica y Genética de Microorganismos, Departamento de Microbiologia e Inmunología, Facultad de Ciencias Biológicas, Universidad Autónoma de Nuevo León, San Nicolas de los Garza, México
| | - Juan S Leon
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Lee-Ann Jaykus
- Department of Food Science, North Carolina State University, Raleigh, North Carolina, USA
| | - Norma Heredia
- Laboratorio de Bioquímica y Genética de Microorganismos, Departamento de Microbiologia e Inmunología, Facultad de Ciencias Biológicas, Universidad Autónoma de Nuevo León, San Nicolas de los Garza, México
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29
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Doster E, Thomas KM, Weinroth MD, Parker JK, Crone KK, Arthur TM, Schmidt JW, Wheeler TL, Belk KE, Morley PS. Metagenomic Characterization of the Microbiome and Resistome of Retail Ground Beef Products. Front Microbiol 2020; 11:541972. [PMID: 33240224 PMCID: PMC7677504 DOI: 10.3389/fmicb.2020.541972] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 10/19/2020] [Indexed: 12/13/2022] Open
Abstract
Ground beef can be a reservoir for a variety of bacteria, including spoilage organisms, and pathogenic foodborne bacteria. These bacteria can exhibit antimicrobial resistance (AMR) which is a public health concern if resistance in pathogens leads to treatment failure in humans. Culture-dependent techniques are commonly used to study individual bacterial species, but these techniques are unable to describe the whole community of microbial species (microbiome) and the profile of AMR genes they carry (resistome), which is critical for getting a holistic perspective of AMR. The objective of this study was to characterize the microbiome and resistome of retail ground beef products labeled as coming from conventional or raised without antibiotics (RWA) production systems. Sixteen ground beef products were purchased from 6 retail grocery outlets in Fort Collins, CO, half of which were labeled as produced from cattle raised conventionally and half of products were from RWA production. Total DNA was extracted and isolated from each sample and subjected to 16S rRNA amplicon sequencing for microbiome characterization and target-enriched shotgun sequencing to characterize the resistome. Differences in the microbiome and resistome of RWA and conventional ground beef were analyzed using the R programming software. Our results suggest that the resistome and microbiome of retail ground beef products with RWA packaging labels do not differ from products that do not carry claims regarding antimicrobial drug exposures during cattle production. The resistome predominantly consisted of tetracycline resistance making up more than 90% of reads mapped to resistance gene accessions in our samples. Firmicutes and Proteobacteria predominated in the microbiome of all samples (69.6% and 29.0%, respectively), but Proteobacteria composed a higher proportion in ground beef from conventionally raised cattle. In addition, our results suggest that product management, such as packaging type, could exert a stronger influence on the microbiome than the resistome in consumer-ready products. Metagenomic analyses of ground beef is a promising tool to investigate community-wide shifts in retail ground beef. Importantly, however, results from metagenomic sequencing must be carefully considered in parallel with traditional methods to better characterize the risk of AMR in retail products.
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Affiliation(s)
- Enrique Doster
- Texas A&M University, VERO Program, Canyon, TX, United States.,Department of Microbiology, Immunology and Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, United States.,Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, United States
| | - Kevin M Thomas
- Department of Animal Sciences, College of Agricultural Sciences, Colorado State University, Fort Collins, CO, United States
| | - Maggie D Weinroth
- Department of Animal Sciences, College of Agricultural Sciences, Colorado State University, Fort Collins, CO, United States
| | - Jennifer K Parker
- Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, United States
| | - Kathryn K Crone
- Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, United States
| | - Terrance M Arthur
- U.S. Meat Animal Research Center, Agricultural Research Service, United States Department of Agriculture, Clay Center, NE, United States
| | - John W Schmidt
- U.S. Meat Animal Research Center, Agricultural Research Service, United States Department of Agriculture, Clay Center, NE, United States
| | - Tommy L Wheeler
- U.S. Meat Animal Research Center, Agricultural Research Service, United States Department of Agriculture, Clay Center, NE, United States
| | - Keith E Belk
- Department of Animal Sciences, College of Agricultural Sciences, Colorado State University, Fort Collins, CO, United States
| | - Paul S Morley
- Texas A&M University, VERO Program, Canyon, TX, United States.,Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, United States
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30
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A unified catalog of 204,938 reference genomes from the human gut microbiome. Nat Biotechnol 2020; 39:105-114. [PMID: 32690973 PMCID: PMC7801254 DOI: 10.1038/s41587-020-0603-3] [Citation(s) in RCA: 538] [Impact Index Per Article: 134.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Accepted: 05/31/2020] [Indexed: 01/08/2023]
Abstract
Comprehensive, high-quality reference genomes are required for functional characterization and taxonomic assignment of the human gut microbiota. We present the Unified Human Gastrointestinal Genome (UHGG) collection, comprising 204,938 nonredundant genomes from 4,644 gut prokaryotes. These genomes encode >170 million protein sequences, which we collated in the Unified Human Gastrointestinal Protein (UHGP) catalog. The UHGP more than doubles the number of gut proteins in comparison to those present in the Integrated Gene Catalog. More than 70% of the UHGG species lack cultured representatives, and 40% of the UHGP lack functional annotations. Intraspecies genomic variation analyses revealed a large reservoir of accessory genes and single-nucleotide variants, many of which are specific to individual human populations. The UHGG and UHGP collections will enable studies linking genotypes to phenotypes in the human gut microbiome. More than 200,000 gut prokaryotic reference genomes and the proteins they encode are collated, providing comprehensive resources for microbiome researchers.
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31
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Slizovskiy IB, Mukherjee K, Dean CJ, Boucher C, Noyes NR. Mobilization of Antibiotic Resistance: Are Current Approaches for Colocalizing Resistomes and Mobilomes Useful? Front Microbiol 2020; 11:1376. [PMID: 32695079 PMCID: PMC7338343 DOI: 10.3389/fmicb.2020.01376] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Accepted: 05/28/2020] [Indexed: 11/16/2022] Open
Abstract
Antimicrobial resistance (AMR) poses a global human and animal health threat, and predicting AMR persistence and transmission remains an intractable challenge. Shotgun metagenomic sequencing can help overcome this by enabling characterization of AMR genes within all bacterial taxa, most of which are uncultivatable in laboratory settings. Shotgun sequencing, therefore, provides a more comprehensive glance at AMR "potential" within samples, i.e., the "resistome." However, the risk inherent within a given resistome is predicated on the genomic context of various AMR genes, including their presence within mobile genetic elements (MGEs). Therefore, resistome risk stratification can be advanced if AMR profiles are considered in light of the flanking mobilizable genomic milieu (e.g., plasmids, integrative conjugative elements (ICEs), phages, and other MGEs). Because such mediators of horizontal gene transfer (HGT) are involved in uptake by pathogens, investigators are increasingly interested in characterizing that resistome fraction in genomic proximity to HGT mediators, i.e., the "mobilome"; we term this "colocalization." We explored the utility of common colocalization approaches using alignment- and assembly-based techniques, on clinical (human) and agricultural (cattle) fecal metagenomes, obtained from antimicrobial use trials. Ordination revealed that tulathromycin-treated cattle experienced a shift in ICE and plasmid composition versus untreated animals, though the resistome was unaffected during the monitoring period. Contrarily, the human resistome and mobilome composition both shifted shortly after antimicrobial administration, though this rebounded to pre-treatment status. Bayesian networks revealed statistical AMR-MGE co-occurrence in 19 and 2% of edges from the cattle and human networks, respectively, suggesting a putatively greater mobility potential of AMR in cattle feces. Conversely, using Mobility Index (MI) and overlap analysis, abundance of de novo-assembled contigs supporting resistomes flanked by MGE increased shortly post-exposure within human metagenomes, though > 40 days after peak dose such contigs were rare (∼2%). MI was not substantially altered by antimicrobial exposure across all cattle metagenomes, ranging 0.5-4.0%. We highlight that current alignment- and assembly-based methods estimating resistome mobility yield contradictory and incomplete results, likely constrained by approach-specific data inputs, and bioinformatic limitations. We discuss recent laboratory and computational advancements that may enhance resistome risk analysis in clinical, regulatory, and commercial applications.
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Affiliation(s)
- Ilya B Slizovskiy
- Food-Centric Corridor, Infectious Disease Laboratory, Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, United States
| | - Kingshuk Mukherjee
- Department of Computer and Information Science and Engineering, The Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL, United States
| | - Christopher J Dean
- Food-Centric Corridor, Infectious Disease Laboratory, Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, United States
| | - Christina Boucher
- Department of Computer and Information Science and Engineering, The Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL, United States
| | - Noelle R Noyes
- Food-Centric Corridor, Infectious Disease Laboratory, Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, United States
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32
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Campos Calero G, Caballero Gómez N, Lavilla Lerma L, Benomar N, Knapp CW, Abriouel H. In silico mapping of microbial communities and stress responses in a porcine slaughterhouse and pork products through its production chain, and the efficacy of HLE disinfectant. Food Res Int 2020; 136:109486. [PMID: 32846568 DOI: 10.1016/j.foodres.2020.109486] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Revised: 06/22/2020] [Accepted: 06/23/2020] [Indexed: 01/10/2023]
Abstract
The use of shotgun metagenomic sequencing to understand ecological-level spread of microbes and their genes has provided new insights for the prevention, surveillance and control of microbial contaminants in the slaughterhouse environment. Here, microbial samples were collected from products and surrounding areas though a porcine slaughter process; shotgun metagenomic DNA-sequencing of these samples revealed a high community diversity within the porcine slaughterhouse and pork products, in zones originating from animal arrival through to the sale zones. Bacteria were more prevalent in the first zones, such as arrival- and anesthesia-zones, and DNA viruses were prevalent in the scorching-and-whip zone, animal products and sale zone. Data revealed the dominance of Firmicutes and Proteobacteria phyla followed by Actinobacteria, with a clear shift in the relative abundance of lactic acid bacteria (mainly Lactobacillus sp.) from early slaughtering steps to Proteobacteria and then to viruses suggesting site-specific community compositions occur in the slaughterhouse. Porcine-type-C oncovirus was the main virus found in slaughterhouse, which causes malignant diseases in animals and humans. As such, to guarantee food safety in a slaughterhouse, a better decipher of ecology and adaptation strategies of microbes becomes crucial. Analysis of functional genes further revealed high abundance of diverse genes associated with stress, especially in early zones (animal and environmental surfaces of arrival zone with 57,710 and 40,806 genes, respectively); SOS responsive genes represented the most prevalent, possibly associated with genomic changes responsible of biofilm formation, stringent response, heat shock, antimicrobial production and antibiotic response. The presence of several antibiotic resistance genes suggests horizontal gene transfer, thus increasing the likelihood for resistance selection in human pathogens. These findings are of great concern, with the suggestion to focus control measures and establish good disinfection strategies to avoid gene spread and microbial contaminants (bacteria and viruses) from the animal surface into the food chain and environment, which was achieved by applying HLE disinfectant after washing with detergent.
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Affiliation(s)
- Guillermo Campos Calero
- Área de Microbiología, Departamento de Ciencias de la Salud, Facultad de Ciencias Experimentales, Universidad de Jaén, 23071 Jaén, Spain
| | - Natacha Caballero Gómez
- Área de Microbiología, Departamento de Ciencias de la Salud, Facultad de Ciencias Experimentales, Universidad de Jaén, 23071 Jaén, Spain
| | - Leyre Lavilla Lerma
- Área de Microbiología, Departamento de Ciencias de la Salud, Facultad de Ciencias Experimentales, Universidad de Jaén, 23071 Jaén, Spain
| | - Nabil Benomar
- Área de Microbiología, Departamento de Ciencias de la Salud, Facultad de Ciencias Experimentales, Universidad de Jaén, 23071 Jaén, Spain
| | - Charles W Knapp
- Centre for Water, Environment, Sustainability & Public Health, Department of Civil and Environmental Engineering, University of Strathclyde, Glasgow, Scotland, United Kingdom
| | - Hikmate Abriouel
- Área de Microbiología, Departamento de Ciencias de la Salud, Facultad de Ciencias Experimentales, Universidad de Jaén, 23071 Jaén, Spain.
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33
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Haley BJ, Kim SW, Salaheen S, Hovingh E, Van Kessel JAS. Differences in the Microbial Community and Resistome Structures of Feces from Preweaned Calves and Lactating Dairy Cows in Commercial Dairy Herds. Foodborne Pathog Dis 2020; 17:494-503. [PMID: 32176535 DOI: 10.1089/fpd.2019.2768] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Preweaned dairy calves and lactating dairy cows are known reservoirs of antibiotic-resistant bacteria. To further understand the differences in the resistomes and microbial communities between the two, we sequenced the metagenomes of fecal composite samples from preweaned dairy calves and lactating dairy cows on 17 commercial dairy farms (n = 34 samples). Results indicated significant differences in the structures of the microbial communities (analysis of similarities [ANOSIM] R = 0.81, p = 0.001) and resistomes (ANOSIM R = 0.93 to 0.96, p = 0.001) between the two age groups. Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria were the predominant members of the communities, but when the groups were compared, Bacteroidetes and Verrumicrobia were significantly more abundant in calf fecal composite samples, whereas Firmicutes, Spirochaetes, Deinococcus-Thermus, Lentisphaerae, Planctomycetes, Chlorofexi, and Saccharibacteria-(TM7) were more abundant in lactating cow samples. Diverse suites of antibiotic resistance genes (ARGs) were identified in all samples, with the most frequently detected being assigned to tetracycline and aminoglycoside resistance. When the two groups were compared, ARGs were significantly more abundant in composite fecal samples from calves than those from lactating cows (calf median ARG abundance = 1.8 × 100 ARG/16S ribosomal RNA [rRNA], cow median ARG abundance = 1.7 × 10-1 ARG/16S rRNA) and at the antibiotic resistance class level, the relative abundance of tetracycline, trimethoprim, aminoglycoside, macrolide-lincosamide-streptogramin B, β-lactam, and phenicol resistance genes was significantly higher in calf samples than in cow samples. Results of this study indicate that composite feces from preweaned calves harbor different bacterial communities and resistomes than composite feces from lactating cows, with a greater abundance of resistance genes detected in preweaned calf feces.
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Affiliation(s)
- Bradd J Haley
- Environmental Microbial and Food Safety Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland
| | - Seon-Woo Kim
- Environmental Microbial and Food Safety Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland
| | - Serajus Salaheen
- Environmental Microbial and Food Safety Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland
| | - Ernest Hovingh
- Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, Pennsylvania
| | - Jo Ann S Van Kessel
- Environmental Microbial and Food Safety Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland
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34
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Andermann T, Torres Jiménez MF, Matos-Maraví P, Batista R, Blanco-Pastor JL, Gustafsson ALS, Kistler L, Liberal IM, Oxelman B, Bacon CD, Antonelli A. A Guide to Carrying Out a Phylogenomic Target Sequence Capture Project. Front Genet 2020; 10:1407. [PMID: 32153629 PMCID: PMC7047930 DOI: 10.3389/fgene.2019.01407] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Accepted: 12/24/2019] [Indexed: 12/17/2022] Open
Abstract
High-throughput DNA sequencing techniques enable time- and cost-effective sequencing of large portions of the genome. Instead of sequencing and annotating whole genomes, many phylogenetic studies focus sequencing effort on large sets of pre-selected loci, which further reduces costs and bioinformatic challenges while increasing coverage. One common approach that enriches loci before sequencing is often referred to as target sequence capture. This technique has been shown to be applicable to phylogenetic studies of greatly varying evolutionary depth. Moreover, it has proven to produce powerful, large multi-locus DNA sequence datasets suitable for phylogenetic analyses. However, target capture requires careful considerations, which may greatly affect the success of experiments. Here we provide a simple flowchart for designing phylogenomic target capture experiments. We discuss necessary decisions from the identification of target loci to the final bioinformatic processing of sequence data. We outline challenges and solutions related to the taxonomic scope, sample quality, and available genomic resources of target capture projects. We hope this review will serve as a useful roadmap for designing and carrying out successful phylogenetic target capture studies.
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Affiliation(s)
- Tobias Andermann
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
- Gothenburg Global Biodiversity Centre, Gothenburg, Sweden
| | - Maria Fernanda Torres Jiménez
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
- Gothenburg Global Biodiversity Centre, Gothenburg, Sweden
| | - Pável Matos-Maraví
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
- Gothenburg Global Biodiversity Centre, Gothenburg, Sweden
- Institute of Entomology, Biology Centre of the Czech Academy of Sciences, České Budějovice, Czechia
| | - Romina Batista
- Gothenburg Global Biodiversity Centre, Gothenburg, Sweden
- Programa de Pós-Graduação em Genética, Conservação e Biologia Evolutiva, PPG GCBEv–Instituto Nacional de Pesquisas da Amazônia—INPA Campus II, Manaus, Brazil
- Coordenação de Zoologia, Museu Paraense Emílio Goeldi, Belém, Brazil
| | - José L. Blanco-Pastor
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
- INRAE, Centre Nouvelle-Aquitaine-Poitiers, Lusignan, France
| | | | - Logan Kistler
- Department of Anthropology, National Museum of Natural History, Smithsonian Institution, Washington, DC, United States
| | - Isabel M. Liberal
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Bengt Oxelman
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
- Gothenburg Global Biodiversity Centre, Gothenburg, Sweden
| | - Christine D. Bacon
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
- Gothenburg Global Biodiversity Centre, Gothenburg, Sweden
| | - Alexandre Antonelli
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
- Gothenburg Global Biodiversity Centre, Gothenburg, Sweden
- Royal Botanic Gardens, Kew, Richmond-Surrey, United Kingdom
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35
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Discovery of Bat Coronaviruses through Surveillance and Probe Capture-Based Next-Generation Sequencing. mSphere 2020; 5:5/1/e00807-19. [PMID: 31996413 PMCID: PMC6992374 DOI: 10.1128/msphere.00807-19] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Coronaviruses (CoVs) of bat origin have caused two pandemics in this century. Severe acute respiratory syndrome (SARS)-CoV and Middle East respiratory syndrome (MERS)-CoV both originated from bats, and it is highly likely that bat coronaviruses will cause future outbreaks. Active surveillance is both urgent and essential to predict and mitigate the emergence of these viruses in humans. Next-generation sequencing (NGS) is currently the preferred methodology for virus discovery to ensure unbiased sequencing of bat CoVs, considering their high genetic diversity. However, unbiased NGS is an expensive methodology and is prone to missing low-abundance CoV sequences due to the high background level of nonviral sequences present in surveillance field samples. Here, we employ a capture-based NGS approach using baits targeting most of the CoV species. Using this technology, we effectively reduced sequencing costs by increasing the sensitivity of detection. We discovered nine full genomes of bat CoVs in this study and revealed great genetic diversity for eight of them.IMPORTANCE Active surveillance is both urgent and essential to predict and mitigate the emergence of bat-origin CoV in humans and livestock. However, great genetic diversity increases the chance of homologous recombination among CoVs. Performing targeted PCR, a common practice for many surveillance studies, would not reflect this diversity. NGS, on the other hand, is an expensive methodology and is prone to missing low-abundance CoV sequences. Here, we employ a capture-based NGS approach using baits targeting all CoVs. Our work demonstrates that targeted, cost-effective, large-scale, genome-level surveillance of bat CoVs is now highly feasible.
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36
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Capturing the Resistome: a Targeted Capture Method To Reveal Antibiotic Resistance Determinants in Metagenomes. Antimicrob Agents Chemother 2019; 64:AAC.01324-19. [PMID: 31611361 PMCID: PMC7187591 DOI: 10.1128/aac.01324-19] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Accepted: 10/01/2019] [Indexed: 12/31/2022] Open
Abstract
Identification of the nucleotide sequences encoding antibiotic resistance elements and determination of their association with antibiotic resistance are critical to improve surveillance and monitor trends in antibiotic resistance. Current methods to study antibiotic resistance in various environments rely on extensive deep sequencing or laborious culturing of fastidious organisms, both of which are heavily time-consuming operations. An accurate and sensitive method to identify both rare and common resistance elements in complex metagenomic samples is needed. Referencing the sequences in the Comprehensive Antibiotic Resistance Database, we designed a set of 37,826 probes to specifically target over 2,000 nucleotide sequences associated with antibiotic resistance in clinically relevant bacteria. Testing of this probe set on DNA libraries generated from multidrug-resistant bacteria to selectively capture resistance genes reproducibly produced higher numbers of reads on target at a greater length of coverage than shotgun sequencing. We also identified additional resistance gene sequences from human gut microbiome samples that sequencing alone was not able to detect. Our method to capture the resistome enables a sensitive means of gene detection in diverse environments where genes encoding antibiotic resistance represent less than 0.1% of the metagenome.
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37
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Peto L, Fawcett NJ, Crook DW, Peto TEA, Llewelyn MJ, Walker AS. Selective culture enrichment and sequencing of feces to enhance detection of antimicrobial resistance genes in third-generation cephalosporin resistant Enterobacteriaceae. PLoS One 2019; 14:e0222831. [PMID: 31703058 PMCID: PMC6839868 DOI: 10.1371/journal.pone.0222831] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2019] [Accepted: 09/07/2019] [Indexed: 01/02/2023] Open
Abstract
Metagenomic sequencing of fecal DNA can usefully characterise an individual's intestinal resistome but is limited by its inability to detect important pathogens that may be present at low abundance, such as carbapenemase or extended-spectrum beta-lactamase producing Enterobacteriaceae. Here we aimed to develop a hybrid protocol to improve detection of resistance genes in Enterobacteriaceae by using a short period of culture enrichment prior to sequencing of DNA extracted directly from the enriched sample. Volunteer feces were spiked with carbapenemase-producing Enterobacteriaceae and incubated in selective broth culture for 6 hours before sequencing. Different DNA extraction methods were compared, including a plasmid extraction protocol to increase the detection of plasmid-associated resistance genes. Although enrichment prior to sequencing increased the detection of carbapenemase genes, the differing growth characteristics of the spike organisms precluded accurate quantification of their concentration prior to culture. Plasmid extraction increased detection of resistance genes present on plasmids, but the effects were heterogeneous and dependent on plasmid size. Our results demonstrate methods of improving the limit of detection of selected resistance mechanisms in a fecal resistome assay, but they also highlight the difficulties in using these techniques for accurate quantification and should inform future efforts to achieve this goal.
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Affiliation(s)
- Leon Peto
- National Institute for Health Research (NIHR) Health Protection Research Unit on Healthcare Associated Infections and Antimicrobial Resistance, John Radcliffe Hospital, Oxford, England, United Kingdom
- Nuffield Department of Medicine, University of Oxford, Oxford, England, United Kingdom
- * E-mail:
| | - Nicola J. Fawcett
- National Institute for Health Research (NIHR) Health Protection Research Unit on Healthcare Associated Infections and Antimicrobial Resistance, John Radcliffe Hospital, Oxford, England, United Kingdom
- Nuffield Department of Medicine, University of Oxford, Oxford, England, United Kingdom
| | - Derrick W. Crook
- National Institute for Health Research (NIHR) Health Protection Research Unit on Healthcare Associated Infections and Antimicrobial Resistance, John Radcliffe Hospital, Oxford, England, United Kingdom
- Nuffield Department of Medicine, University of Oxford, Oxford, England, United Kingdom
- National Infection Service, Public Health England, Colindale, London, England, United Kingdom
| | - Tim E. A. Peto
- National Institute for Health Research (NIHR) Health Protection Research Unit on Healthcare Associated Infections and Antimicrobial Resistance, John Radcliffe Hospital, Oxford, England, United Kingdom
- Nuffield Department of Medicine, University of Oxford, Oxford, England, United Kingdom
| | - Martin J. Llewelyn
- Department of Global Health and Infection, Brighton and Sussex Medical School, Falmer, Sussex, England, United Kingdom
- Department of Microbiology and Infection, Brighton and Sussex University Hospitals NHS Trust, Brighton, England, United Kingdom
| | - A. Sarah Walker
- National Institute for Health Research (NIHR) Health Protection Research Unit on Healthcare Associated Infections and Antimicrobial Resistance, John Radcliffe Hospital, Oxford, England, United Kingdom
- Nuffield Department of Medicine, University of Oxford, Oxford, England, United Kingdom
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Doster E, Rovira P, Noyes NR, Burgess BA, Yang X, Weinroth MD, Linke L, Magnuson R, Boucher C, Belk KE, Morley PS. A Cautionary Report for Pathogen Identification Using Shotgun Metagenomics; A Comparison to Aerobic Culture and Polymerase Chain Reaction for Salmonella enterica Identification. Front Microbiol 2019; 10:2499. [PMID: 31736924 PMCID: PMC6838018 DOI: 10.3389/fmicb.2019.02499] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Accepted: 10/16/2019] [Indexed: 12/19/2022] Open
Abstract
This study was conducted to compare aerobic culture, polymerase chain reaction (PCR), lateral flow immunoassay (LFI), and shotgun metagenomics for identification of Salmonella enterica in feces collected from feedlot cattle. Samples were analyzed in parallel using all four tests. Results from aerobic culture and PCR were 100% concordant and indicated low S. enterica prevalence (3/60 samples positive). Although low S. enterica prevalence restricted formal statistical comparisons, LFI and deep metagenomic sequencing results were discordant with these results. Specifically, metagenomic analysis using k-mer-based classification against the RefSeq database indicated that 11/60 of samples contained sequence reads that matched to the S. enterica genome and uniquely identified this species of bacteria within the sample. However, further examination revealed that plasmid sequences were often included with bacterial genomic sequence data submitted to NCBI, which can lead to incorrect taxonomic classification. To circumvent this classification problem, we separated all plasmid sequences included in bacterial RefSeq genomes and reassigned them to a unique taxon so that they would not be uniquely associated with specific bacterial species such as S. enterica. Using this revised database and taxonomic structure, we found that only 6/60 samples contained sequences specific for S. enterica, suggesting increased relative specificity. Reads identified as S. enterica in these six samples were further evaluated using BLAST and NCBI's nr/nt database, which identified that only 2/60 samples contained reads exclusive to S. enterica chromosomal genomes. These two samples were culture- and PCR-negative, suggesting that even deep metagenomic sequencing suffers from lower sensitivity and specificity in comparison to more traditional pathogen detection methods. Additionally, no sample reads were taxonomically classified as S. enterica with two other metagenomic tools, Metagenomic Intra-species Diversity Analysis System (MIDAS) and Metagenomic Phylogenetic Analysis 2 (MetaPhlAn2). This study re-affirmed that the traditional techniques of aerobic culture and PCR provide similar results for S. enterica identification in cattle feces. On the other hand, metagenomic results are highly influenced by the classification method and reference database employed. These results highlight the nuances of computational detection of species-level sequences within short-read metagenomic sequence data, and emphasize the need for cautious interpretation of such results.
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Affiliation(s)
- Enrique Doster
- Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, United States
| | - Pablo Rovira
- Instituto Nacional de Investigacion Agropecuaria, Treinta y Tres, Uruguay
| | - Noelle R. Noyes
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN, United States
| | - Brandy A. Burgess
- Department of Population Health, University of Georgia, Athens, GA, United States
| | - Xiang Yang
- Department of Animal Science, University of California, Davis, Davis, CA, United States
| | - Margaret D. Weinroth
- Department of Animal Sciences, Colorado State University, Fort Collins, CO, United States
| | - Lyndsey Linke
- Department of Clinical Sciences, Colorado State University, Fort Collins, CO, United States
| | - Roberta Magnuson
- Department of Clinical Sciences, Colorado State University, Fort Collins, CO, United States
| | - Christina Boucher
- Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, United States
| | - Keith E. Belk
- Department of Animal Sciences, Colorado State University, Fort Collins, CO, United States
| | - Paul S. Morley
- Veterinary Education, Research, and Outreach Center, West Texas A&M University, Canyon, TX, United States
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Horizontal Gene Transfer and Acquired Antibiotic Resistance in Salmonella enterica Serovar Heidelberg following In Vitro Incubation in Broiler Ceca. Appl Environ Microbiol 2019; 85:AEM.01903-19. [PMID: 31471306 DOI: 10.1128/aem.01903-19] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Accepted: 08/28/2019] [Indexed: 12/13/2022] Open
Abstract
The chicken gastrointestinal tract harbors microorganisms that play a role in the health and disease status of the host. The cecum is the part of the gut that carries the highest microbial densities, has the longest residence time of digesta, and is a vital site for urea recycling and water regulation. Therefore, the cecum provides a rich environment for bacteria to horizontally transfer genes between one another via mobile genetic elements such as plasmids and bacteriophages. In this study, we used broiler chicken cecum as a model to investigate antibiotic resistance genes that can be transferred in vitro from cecal flora to Salmonella enterica serovar Heidelberg. We used whole-genome sequencing and resistome enrichment to decipher the interactions between S Heidelberg, the gut microbiome, and acquired antibiotic resistance. After 48 h of incubation of ceca under microaerophilic conditions, we recovered one S Heidelberg isolate with an acquired IncK2 plasmid (88 kb) carrying an extended-spectrum-β-lactamase gene (bla CMY-2). In vitro, this plasmid was transferable between Escherichia coli and S Heidelberg strains but transfer was unsuccessful between S Heidelberg strains. An in-depth genetic characterization of transferred plasmids suggests that they share significant homology with P1-like phages. This study contributes to our understanding of horizontal gene transfer between an important foodborne pathogen and the chicken gut microbiome.IMPORTANCE S. Heidelberg is a clinically important serovar, linked to foodborne illness and among the top 5 serovars isolated from poultry in the United States and Canada. Acquisition of new genetic material from the microbial flora in the gastrointestinal tract of food animals, including broilers, may contribute to increased fitness of pathogens like S. Heidelberg and may increase their level of antibiotic tolerance. Therefore, it is critical to gain a better understanding of the interactions that occur between important pathogens and the commensals present in the animal gut and other agroecosystems. In this report, we show that the native flora in broiler ceca were capable of transferring mobile genetic elements carrying the AmpC β-lactamase (bla CMY-2) gene to an important foodborne pathogen, S Heidelberg. The potential role for bacteriophage transduction is also discussed.
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Gweon HS, Shaw LP, Swann J, De Maio N, AbuOun M, Niehus R, Hubbard ATM, Bowes MJ, Bailey MJ, Peto TEA, Hoosdally SJ, Walker AS, Sebra RP, Crook DW, Anjum MF, Read DS, Stoesser N. The impact of sequencing depth on the inferred taxonomic composition and AMR gene content of metagenomic samples. ENVIRONMENTAL MICROBIOME 2019; 14:7. [PMID: 33902704 PMCID: PMC8204541 DOI: 10.1186/s40793-019-0347-1] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Accepted: 09/28/2019] [Indexed: 05/18/2023]
Abstract
BACKGROUND Shotgun metagenomics is increasingly used to characterise microbial communities, particularly for the investigation of antimicrobial resistance (AMR) in different animal and environmental contexts. There are many different approaches for inferring the taxonomic composition and AMR gene content of complex community samples from shotgun metagenomic data, but there has been little work establishing the optimum sequencing depth, data processing and analysis methods for these samples. In this study we used shotgun metagenomics and sequencing of cultured isolates from the same samples to address these issues. We sampled three potential environmental AMR gene reservoirs (pig caeca, river sediment, effluent) and sequenced samples with shotgun metagenomics at high depth (~ 200 million reads per sample). Alongside this, we cultured single-colony isolates of Enterobacteriaceae from the same samples and used hybrid sequencing (short- and long-reads) to create high-quality assemblies for comparison to the metagenomic data. To automate data processing, we developed an open-source software pipeline, 'ResPipe'. RESULTS Taxonomic profiling was much more stable to sequencing depth than AMR gene content. 1 million reads per sample was sufficient to achieve < 1% dissimilarity to the full taxonomic composition. However, at least 80 million reads per sample were required to recover the full richness of different AMR gene families present in the sample, and additional allelic diversity of AMR genes was still being discovered in effluent at 200 million reads per sample. Normalising the number of reads mapping to AMR genes using gene length and an exogenous spike of Thermus thermophilus DNA substantially changed the estimated gene abundance distributions. While the majority of genomic content from cultured isolates from effluent was recoverable using shotgun metagenomics, this was not the case for pig caeca or river sediment. CONCLUSIONS Sequencing depth and profiling method can critically affect the profiling of polymicrobial animal and environmental samples with shotgun metagenomics. Both sequencing of cultured isolates and shotgun metagenomics can recover substantial diversity that is not identified using the other methods. Particular consideration is required when inferring AMR gene content or presence by mapping metagenomic reads to a database. ResPipe, the open-source software pipeline we have developed, is freely available ( https://gitlab.com/hsgweon/ResPipe ).
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Affiliation(s)
- H Soon Gweon
- Harborne Building, School of Biological Sciences, University of Reading, Reading, RG6 6AS, UK.
- Centre for Ecology & Hydrology, Wallingford, Oxfordshire, OX10 8BB, UK.
| | - Liam P Shaw
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Jeremy Swann
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Nicola De Maio
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Manal AbuOun
- Department of Bacteriology, Animal and Plant Health Agency, Addlestone, Surrey, KT15 3NB, UK
| | - Rene Niehus
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Mike J Bowes
- Centre for Ecology & Hydrology, Wallingford, Oxfordshire, OX10 8BB, UK
| | - Mark J Bailey
- Centre for Ecology & Hydrology, Wallingford, Oxfordshire, OX10 8BB, UK
| | - Tim E A Peto
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- NIHR Health Protection Research Unit (HPRU) in Healthcare-associated Infections and Antimicrobial Resistance at University of Oxford in partnership with Public Health England, Oxford, UK
| | | | - A Sarah Walker
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- NIHR Health Protection Research Unit (HPRU) in Healthcare-associated Infections and Antimicrobial Resistance at University of Oxford in partnership with Public Health England, Oxford, UK
| | - Robert P Sebra
- Department of Genetics and Genomics, Icahn School of Medicine at Mt Sinai, New York, NY, USA
| | - Derrick W Crook
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- NIHR Health Protection Research Unit (HPRU) in Healthcare-associated Infections and Antimicrobial Resistance at University of Oxford in partnership with Public Health England, Oxford, UK
| | - Muna F Anjum
- Department of Bacteriology, Animal and Plant Health Agency, Addlestone, Surrey, KT15 3NB, UK
| | - Daniel S Read
- Centre for Ecology & Hydrology, Wallingford, Oxfordshire, OX10 8BB, UK
| | - Nicole Stoesser
- Nuffield Department of Medicine, University of Oxford, Oxford, UK.
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41
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Lakin SM, Kuhnle A, Alipanahi B, Noyes NR, Dean C, Muggli M, Raymond R, Abdo Z, Prosperi M, Belk KE, Morley PS, Boucher C. Hierarchical Hidden Markov models enable accurate and diverse detection of antimicrobial resistance sequences. Commun Biol 2019; 2:294. [PMID: 31396574 PMCID: PMC6684577 DOI: 10.1038/s42003-019-0545-9] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Accepted: 07/08/2019] [Indexed: 12/13/2022] Open
Abstract
The characterization of antimicrobial resistance genes from high-throughput sequencing data has become foundational in public health research and regulation. This requires mapping sequence reads to databases of known antimicrobial resistance genes to determine the genes present in the sample. Mapping sequence reads to known genes is traditionally accomplished using alignment. Alignment methods have high specificity but are limited in their ability to detect sequences that are divergent from the reference database, which can result in a substantial false negative rate. We address this shortcoming through the creation of Meta-MARC, which enables detection of diverse resistance sequences using hierarchical, DNA-based Hidden Markov Models. We first describe Meta-MARC and then demonstrate its efficacy on simulated and functional metagenomic datasets. Meta-MARC has higher sensitivity relative to competing methods. This sensitivity allows for detection of sequences that are divergent from known antimicrobial resistance genes. This functionality is imperative to expanding existing antimicrobial gene databases.
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Affiliation(s)
- Steven M Lakin
- 1Department of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO 80523 USA
| | - Alan Kuhnle
- 2Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611 USA
| | - Bahar Alipanahi
- 2Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611 USA
| | - Noelle R Noyes
- 3Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN 55108 USA
| | - Chris Dean
- 1Department of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO 80523 USA
| | - Martin Muggli
- 4Department of Computer Science, Colorado State University, Fort Collins, CO 80523 USA
| | - Rob Raymond
- 4Department of Computer Science, Colorado State University, Fort Collins, CO 80523 USA
| | - Zaid Abdo
- 1Department of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO 80523 USA
| | - Mattia Prosperi
- 5Department of Epidemiology, University of Florida, Gainesville, FL 32611 USA
| | - Keith E Belk
- 6Department of Animal Sciences, Colorado State University, Fort Collins, CO 80523 USA
| | - Paul S Morley
- 7VERO Center, Texas A&M University and West Texas A&M University, Canyon, TX 79016 USA
| | - Christina Boucher
- 2Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611 USA
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42
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Stumpf AK, Vortmann M, Dirks-Hofmeister ME, Moerschbacher BM, Philipp B. Identification of a novel chitinase from Aeromonas hydrophila AH-1N for the degradation of chitin within fungal mycelium. FEMS Microbiol Lett 2019; 366:5266298. [PMID: 30596975 DOI: 10.1093/femsle/fny294] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Accepted: 12/27/2018] [Indexed: 11/14/2022] Open
Abstract
Defined organic waste products are ideal and sustainable secondary feedstocks for production organisms in microbial biotechnology. Chitin from mycelia of fungal fermentation processes represents a homogeneous and constantly available waste product that can, however, not be utilised by typical bacterial production strains. Therefore, enzymes that degrade chitin within fungal mycelia have to be identified and expressed in production organisms. In this study, chitin-degrading bacteria were enriched and isolated from lake water with mycelia of Aspergillus tubingensis as sole organic growth substrate. This approach yielded solely strains of Aeromonas hydrophila. Comparison of the isolated strains with other A. hydrophila strains regarding their chitinolytic activities on fungal mycelia identified strain AH-1N as the best enzyme producer. From this strain, a chitinase (EC:3.2.1.14) was identified by peptide mass fingerprinting. Heterologous expression of the respective gene combined with mass spectrometry showed that the purified enzyme was capable of releasing chitobiose from fungal mycelia with a higher yield than a well-described chitinase from Serratia marcescens. Expression of the newly identified chitinase in biotechnological production strains could be the first step for making fungal mycelium accessible as a secondary feedstock. Additionally, the enrichment strategy proved to be feasible for identifying strains able to degrade fungal chitin.
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Affiliation(s)
- Anna K Stumpf
- Institut für Molekulare Mikrobiologie und Biotechnologie, Westfälische Wilhelms-Universität (WWU) Muenster, Corrensstraße 3, 48149 Münster, Germany
| | - Marina Vortmann
- Institut für Biologie und Biotechnologie der Pflanzen, Westfälische Wilhelms-Universität (WWU) Muenster, Schlossplatz 8, 48143 Münster, Germany
| | | | - Bruno M Moerschbacher
- Institut für Biologie und Biotechnologie der Pflanzen, Westfälische Wilhelms-Universität (WWU) Muenster, Schlossplatz 8, 48143 Münster, Germany
| | - Bodo Philipp
- Institut für Molekulare Mikrobiologie und Biotechnologie, Westfälische Wilhelms-Universität (WWU) Muenster, Corrensstraße 3, 48149 Münster, Germany
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43
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Metsky HC, Siddle KJ, Gladden-Young A, Qu J, Yang DK, Brehio P, Goldfarb A, Piantadosi A, Wohl S, Carter A, Lin AE, Barnes KG, Tully DC, Corleis B, Hennigan S, Barbosa-Lima G, Vieira YR, Paul LM, Tan AL, Garcia KF, Parham LA, Odia I, Eromon P, Folarin OA, Goba A, Simon-Lorière E, Hensley L, Balmaseda A, Harris E, Kwon DS, Allen TM, Runstadler JA, Smole S, Bozza FA, Souza TML, Isern S, Michael SF, Lorenzana I, Gehrke L, Bosch I, Ebel G, Grant DS, Happi CT, Park DJ, Gnirke A, Sabeti PC, Matranga CB. Capturing sequence diversity in metagenomes with comprehensive and scalable probe design. Nat Biotechnol 2019; 37:160-168. [PMID: 30718881 PMCID: PMC6587591 DOI: 10.1038/s41587-018-0006-x] [Citation(s) in RCA: 75] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Accepted: 12/18/2018] [Indexed: 01/24/2023]
Abstract
Metagenomic sequencing has the potential to transform microbial detection and characterization, but new tools are needed to improve its sensitivity. Here we present CATCH, a computational method to enhance nucleic acid capture for enrichment of diverse microbial taxa. CATCH designs optimal probe sets, with a specified number of oligonucleotides, that achieve full coverage of, and scale well with, known sequence diversity. We focus on applying CATCH to capture viral genomes in complex metagenomic samples. We design, synthesize, and validate multiple probe sets, including one that targets the whole genomes of the 356 viral species known to infect humans. Capture with these probe sets enriches unique viral content on average 18-fold, allowing us to assemble genomes that could not be recovered without enrichment, and accurately preserves within-sample diversity. We also use these probe sets to recover genomes from the 2018 Lassa fever outbreak in Nigeria and to improve detection of uncharacterized viral infections in human and mosquito samples. The results demonstrate that CATCH enables more sensitive and cost-effective metagenomic sequencing.
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Affiliation(s)
- Hayden C. Metsky
- grid.66859.34Broad Institute of MIT and Harvard, Cambridge, MA USA ,0000 0001 2341 2786grid.116068.8Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA USA
| | - Katherine J. Siddle
- grid.66859.34Broad Institute of MIT and Harvard, Cambridge, MA USA ,000000041936754Xgrid.38142.3cDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA USA
| | | | - James Qu
- grid.66859.34Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - David K. Yang
- grid.66859.34Broad Institute of MIT and Harvard, Cambridge, MA USA ,000000041936754Xgrid.38142.3cDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA USA
| | - Patrick Brehio
- grid.66859.34Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Andrew Goldfarb
- 000000041936754Xgrid.38142.3cFaculty of Arts and Sciences, Harvard University, Cambridge, MA USA
| | - Anne Piantadosi
- grid.66859.34Broad Institute of MIT and Harvard, Cambridge, MA USA ,0000 0004 0386 9924grid.32224.35Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA USA
| | - Shirlee Wohl
- grid.66859.34Broad Institute of MIT and Harvard, Cambridge, MA USA ,000000041936754Xgrid.38142.3cDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA USA
| | - Amber Carter
- grid.66859.34Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Aaron E. Lin
- grid.66859.34Broad Institute of MIT and Harvard, Cambridge, MA USA ,000000041936754Xgrid.38142.3cDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA USA
| | - Kayla G. Barnes
- grid.66859.34Broad Institute of MIT and Harvard, Cambridge, MA USA ,000000041936754Xgrid.38142.3cDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA USA ,000000041936754Xgrid.38142.3cDepartment of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA USA
| | - Damien C. Tully
- 0000 0004 0489 3491grid.461656.6The Ragon Institute of MGH, MIT and Harvard, Cambridge, MA USA
| | - Bjӧrn Corleis
- 0000 0004 0489 3491grid.461656.6The Ragon Institute of MGH, MIT and Harvard, Cambridge, MA USA
| | - Scott Hennigan
- 0000 0004 0378 6934grid.416511.6Massachusetts Department of Public Health, Boston, MA USA
| | - Giselle Barbosa-Lima
- 0000 0001 0723 0931grid.418068.3Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro, Rio de Janeiro, Brazil
| | - Yasmine R. Vieira
- 0000 0001 0723 0931grid.418068.3Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro, Rio de Janeiro, Brazil
| | - Lauren M. Paul
- 0000 0001 0647 2963grid.255962.fDepartment of Biological Sciences, College of Arts and Sciences, Florida Gulf Coast University, Fort Myers, FL USA
| | - Amanda L. Tan
- 0000 0001 0647 2963grid.255962.fDepartment of Biological Sciences, College of Arts and Sciences, Florida Gulf Coast University, Fort Myers, FL USA
| | - Kimberly F. Garcia
- 0000 0001 2297 2829grid.10601.36Instituto de Investigacion en Microbiologia, Universidad Nacional Autónoma de Honduras, Tegucigalpa, Honduras
| | - Leda A. Parham
- 0000 0001 2297 2829grid.10601.36Instituto de Investigacion en Microbiologia, Universidad Nacional Autónoma de Honduras, Tegucigalpa, Honduras
| | - Ikponmwosa Odia
- Institute of Lassa Fever Research and Control, Irrua Specialist Teaching Hospital, Irrua, Nigeria
| | - Philomena Eromon
- grid.442553.1African Center of Excellence for Genomics of Infectious Disease (ACEGID), Redeemer’s University, Ede, Nigeria
| | - Onikepe A. Folarin
- grid.442553.1African Center of Excellence for Genomics of Infectious Disease (ACEGID), Redeemer’s University, Ede, Nigeria ,grid.442553.1Department of Biological Sciences, College of Natural Sciences, Redeemer’s University, Ede, Nigeria
| | - Augustine Goba
- Lassa Fever Laboratory, Kenema Government Hospital, Kenema, Sierra Leone
| | | | - Etienne Simon-Lorière
- 0000 0001 2353 6535grid.428999.7Evolutionary Genomics of RNA Viruses, Virology Department, Institut Pasteur, Paris, France
| | - Lisa Hensley
- 0000 0001 2164 9667grid.419681.3Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, US National Institutes of Health, Frederick, MD USA
| | - Angel Balmaseda
- Laboratorio Nacional de Virología, Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua, Nicaragua
| | - Eva Harris
- 0000 0001 2181 7878grid.47840.3fDivision of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, Berkeley, CA USA
| | - Douglas S. Kwon
- 0000 0004 0386 9924grid.32224.35Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA USA ,0000 0004 0489 3491grid.461656.6The Ragon Institute of MGH, MIT and Harvard, Cambridge, MA USA
| | - Todd M. Allen
- 0000 0004 0489 3491grid.461656.6The Ragon Institute of MGH, MIT and Harvard, Cambridge, MA USA
| | - Jonathan A. Runstadler
- 0000 0004 1936 7531grid.429997.8Department of Infectious Disease and Global Health, Cummings School of Veterinary Medicine, Tufts University, North Grafton, MA USA
| | - Sandra Smole
- 0000 0004 0378 6934grid.416511.6Massachusetts Department of Public Health, Boston, MA USA
| | - Fernando A. Bozza
- 0000 0001 0723 0931grid.418068.3Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro, Rio de Janeiro, Brazil
| | - Thiago M. L. Souza
- 0000 0001 0723 0931grid.418068.3Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro, Rio de Janeiro, Brazil
| | - Sharon Isern
- 0000 0001 0647 2963grid.255962.fDepartment of Biological Sciences, College of Arts and Sciences, Florida Gulf Coast University, Fort Myers, FL USA
| | - Scott F. Michael
- 0000 0001 0647 2963grid.255962.fDepartment of Biological Sciences, College of Arts and Sciences, Florida Gulf Coast University, Fort Myers, FL USA
| | - Ivette Lorenzana
- 0000 0001 2297 2829grid.10601.36Instituto de Investigacion en Microbiologia, Universidad Nacional Autónoma de Honduras, Tegucigalpa, Honduras
| | - Lee Gehrke
- 0000 0001 2341 2786grid.116068.8Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA USA ,000000041936754Xgrid.38142.3cDepartment of Microbiology and Immunobiology, Harvard Medical School, Boston, MA USA
| | - Irene Bosch
- 0000 0001 2341 2786grid.116068.8Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA USA
| | - Gregory Ebel
- 0000 0004 1936 8083grid.47894.36Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO USA
| | - Donald S. Grant
- Lassa Fever Laboratory, Kenema Government Hospital, Kenema, Sierra Leone ,0000 0001 2290 9707grid.442296.fCollege of Medicine and Allied Health Sciences, University of Sierra Leone, Freetown, Sierra Leone
| | - Christian T. Happi
- 000000041936754Xgrid.38142.3cDepartment of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA USA ,Institute of Lassa Fever Research and Control, Irrua Specialist Teaching Hospital, Irrua, Nigeria ,grid.442553.1African Center of Excellence for Genomics of Infectious Disease (ACEGID), Redeemer’s University, Ede, Nigeria ,grid.442553.1Department of Biological Sciences, College of Natural Sciences, Redeemer’s University, Ede, Nigeria
| | - Daniel J. Park
- grid.66859.34Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Andreas Gnirke
- grid.66859.34Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Pardis C. Sabeti
- grid.66859.34Broad Institute of MIT and Harvard, Cambridge, MA USA ,000000041936754Xgrid.38142.3cDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA USA ,000000041936754Xgrid.38142.3cDepartment of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA USA ,0000 0001 2167 1581grid.413575.1Howard Hughes Medical Institute, Chevy Chase, MD USA
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44
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Exploring Foodborne Pathogen Ecology and Antimicrobial Resistance in the Light of Shotgun Metagenomics. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2018; 1918:229-245. [PMID: 30580413 DOI: 10.1007/978-1-4939-9000-9_19] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
In this chapter, applications of shotgun metagenomics for taxonomic profiling and functional investigation of food microbial communities with a focus on antimicrobial resistance (AMR) were overviewed in the light of last data in the field. Potentialities of metagenomic approach, along with the challenges encountered for a wider and routinely use in food safety was discussed.
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45
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Campos Calero G, Caballero Gómez N, Benomar N, Pérez Montoro B, Knapp CW, Gálvez A, Abriouel H. Deciphering Resistome and Virulome Diversity in a Porcine Slaughterhouse and Pork Products Through Its Production Chain. Front Microbiol 2018; 9:2099. [PMID: 30258416 PMCID: PMC6144875 DOI: 10.3389/fmicb.2018.02099] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Accepted: 08/16/2018] [Indexed: 12/11/2022] Open
Abstract
We aimed to better understand resistome and virulome patterns on animal and process-area surfaces through a pig slaughterhouse to track possible contamination within the food production chain. Culture-dependent methods revealed high levels of microbial contamination, corresponding to mesophilic and pathogenic bacteria on both the animal and process-area surfaces mainly in the anesthesia (AA and AS) zone followed by “scorching and whip” (FA and FS) zone and also in the end products. To evaluate the potential risk of antibiotic resistance and virulence determinants, shotgun metagenomic DNA-sequencing of isolates from selected areas/products uncovered a high diversity and richness of antibiotic resistance genes (ARGs): 55–62 genes in the anesthesia area (AA and AS) and 35–40 in “animal-arrival zone” (MA and MS). The “scorching and whip” (FA and FS) area, however, exhibited lowered abundance of ARGs (1–6), indicating that the scalding and depilating process (an intermediate zone between “anesthesia” and “scorching and whip”) significantly decreased bacterial load by 1–3 log10 but also diminished the resistome. The high prevalence of antibiotic-inactivating enzyme genes in the “animal-arrival zone” (60–65%) and “anesthesia” area (56%) were mainly represented by those for aminoglycoside (46–51%) and lincosamide (14–19%) resistance, which did not reflect selective pressures by antibiotics most commonly used in pig therapy—tetracyclines and beta-lactams. Contrary to ARGs, greater number of virulence resistance genes were detected after evisceration in some products such as kidney, which reflected the poor hygienic practices. More than 19 general virulence features—mainly adherence, secretion system, chemotaxis and motility, invasion and motility were detected in some products. However, immune evasion determinants were detected in almost all samples analyzed from the beginning of the process, with highest amounts found from the anesthesia area. We conclude that there are two main sources of contamination in a pig slaughterhouse: the microorganisms carried on the animals’ hide, and those from the evisceration step. As such, focussing control measures, e.g., enhanced disinfection procedures, on these contamination-source areas may reduce risks to food safety and consumer health, since the antibiotic and virulence determinants may spread to end products and the environment; further, ARG and virulence traits can exacerbate pathogen treatments.
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Affiliation(s)
- Guillermo Campos Calero
- Área de Microbiología, Departamento de Ciencias de la Salud, Facultad de Ciencias Experimentales, Universidad de Jaén, Jaén, Spain
| | - Natacha Caballero Gómez
- Área de Microbiología, Departamento de Ciencias de la Salud, Facultad de Ciencias Experimentales, Universidad de Jaén, Jaén, Spain
| | - Nabil Benomar
- Área de Microbiología, Departamento de Ciencias de la Salud, Facultad de Ciencias Experimentales, Universidad de Jaén, Jaén, Spain
| | - Beatriz Pérez Montoro
- Área de Microbiología, Departamento de Ciencias de la Salud, Facultad de Ciencias Experimentales, Universidad de Jaén, Jaén, Spain
| | - Charles W Knapp
- Centre for Water, Environment, Sustainability & Public Health, Department of Civil and Environmental Engineering, University of Strathclyde, Glasgow, United Kingdom
| | - Antonio Gálvez
- Área de Microbiología, Departamento de Ciencias de la Salud, Facultad de Ciencias Experimentales, Universidad de Jaén, Jaén, Spain
| | - Hikmate Abriouel
- Área de Microbiología, Departamento de Ciencias de la Salud, Facultad de Ciencias Experimentales, Universidad de Jaén, Jaén, Spain
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Rutanga JP, Van Puyvelde S, Heroes AS, Muvunyi CM, Jacobs J, Deborggraeve S. 16S metagenomics for diagnosis of bloodstream infections: opportunities and pitfalls. Expert Rev Mol Diagn 2018; 18:749-759. [PMID: 29985081 DOI: 10.1080/14737159.2018.1498786] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
INTRODUCTION Bacterial bloodstream infections (BSI) form a large public health threat worldwide. Current routine diagnosis is based on blood culture (BC) but this technique suffers from limited sensitivity. Molecular diagnostic tools have been developed for identification of bacteria in the blood of BSI patients. 16S metagenomics is an open-ended technique that can detect simultaneously all bacteria in a given sample based on PCR amplification of the 16S ribosomal RNA gene (rDNA) followed by sequencing of the PCR amplicons and taxonomic labeling of the sequence reads at genus or species level. Areas covered: Here we review the studies that have used 16S metagenomics for the identification of bacteria in human blood samples. We also discuss the potential added value of 16S metagenomics in the diagnosis of BSI, challenges as well as future directions for implementation in clinical settings. Expert commentary: 16S metagenomics has the potential to complement conventional BC; however, the technique currently suffers from several technical limitations jeopardizing implementation in routine clinical microbiology laboratories. Further studies are required to assess the cost-efficiency and clinical impact of 16S metagenomics in comparison to BC which remains the gold standard diagnostic method for BSI.
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Affiliation(s)
- Jean Pierre Rutanga
- a College of Science and Technology , University of Rwanda , Kigali , Rwanda.,b Department of Biomedical Sciences , Institute of Tropical Medicine , Antwerp , Belgium.,d Department of Microbiology and Immunology , KU Leuven , Leuven , Belgium
| | - Sandra Van Puyvelde
- b Department of Biomedical Sciences , Institute of Tropical Medicine , Antwerp , Belgium.,c Wellcome Trust Sanger Institute , Hinxton , United Kingdom
| | - Anne-Sophie Heroes
- d Department of Microbiology and Immunology , KU Leuven , Leuven , Belgium.,e Department of Clinical Sciences , Institute of Tropical Medicine , Antwerp , Belgium
| | - Claude Mambo Muvunyi
- f College of Medicine and Health Sciences , University of Rwanda , Kigali , Rwanda
| | - Jan Jacobs
- d Department of Microbiology and Immunology , KU Leuven , Leuven , Belgium.,e Department of Clinical Sciences , Institute of Tropical Medicine , Antwerp , Belgium
| | - Stijn Deborggraeve
- b Department of Biomedical Sciences , Institute of Tropical Medicine , Antwerp , Belgium
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